Index (deeplearning4j-core 0.0.3.3.3.alpha1 API)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

able(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators: Wraps an iterator as an iterable
abs(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
accept(T) - Method in interface org.deeplearning4j.berkeley.Filter
accumulateScore(double) - Method in interface org.deeplearning4j.nn.api.Model: Sets a rolling tally for the score.
accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.BaseLayer
accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
accumulateScore(double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
accumulateScore(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne
accuracy() - Method in class org.deeplearning4j.eval.Evaluation: Accuracy: TP + TN / (P + N)
activate() - Method in interface org.deeplearning4j.nn.api.Layer: Trigger an activation with the last specified input
activate(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Initialize the layer with the given input and return the activation for this layer given this input
activate() - Method in class org.deeplearning4j.nn.layers.BaseLayer
activate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
activate() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
activate() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
activate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
activate() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
activate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
activate(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
activate() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Triggers the activation of the last hidden layer ie: not logistic regression
activate(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Triggers the activation for a given layer
activate(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Triggers the activation of the given layer
activationFromPrevLayer(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Calculate activation from previous layer including pre processing where necessary
activationFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
activationFunction(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
activationMean() - Method in interface org.deeplearning4j.nn.api.Layer: Calculate the mean representation for the activation for this layer
activationMean() - Method in class org.deeplearning4j.nn.layers.BaseLayer
activationMean() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
activationMean() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
adaGrad - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
adaGrad - Variable in class org.deeplearning4j.plot.Tsne
adaGradForVariable - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
adaGradForVariables() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Return the ada grad look up table
adaGradForVariables() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
adagradResetIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
add(E, double) - Method in class org.deeplearning4j.berkeley.PriorityQueue
add(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
add(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
add(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
add(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
add(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
add(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
add(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Increments the entry specified by actual and predicted by one.
add(T, T, int) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Increments the entry specified by actual and predicted by count.
add(ConfusionMatrix<T>) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Adds the entries from another confusion matrix to this one.
add(E) - Method in class org.deeplearning4j.util.DiskBasedQueue
add(Object, int) - Method in class org.deeplearning4j.util.Index
add(Object) - Method in class org.deeplearning4j.util.Index
add(Pair<K, V>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Adds the specified element to this applyTransformToDestination if it is not already present (optional operation).
add(K, V) - Method in class org.deeplearning4j.util.MultiDimensionalSet
addAll(Collection<? extends E>) - Method in class org.deeplearning4j.util.DiskBasedQueue
addAll(Collection<? extends Pair<K, V>>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Adds all of the elements in the specified collection to this applyTransformToDestination if they're not already present (optional operation).
addClusterInfo(String) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
addColumn(List<String>) - Method in class org.deeplearning4j.util.StringGrid
addColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addExp(float[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
addExp_Old(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Similar to logAdd, but without the final log.
addi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
addi(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addi(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addi(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
addi(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addiColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addiRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addNewClusterWithCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
addNewClusterWithCenter(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
addPoint(INDArray) - Method in class org.deeplearning4j.clustering.Cluster
addPoint(INDArray, boolean) - Method in class org.deeplearning4j.clustering.Cluster
addPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
addPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.Cluster
addPoint(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
addPoint(INDArray, boolean) - Method in class org.deeplearning4j.clustering.ClusterSet
addPoints(List<INDArray>) - Method in class org.deeplearning4j.clustering.ClusterSet
addPoints(List<INDArray>, boolean) - Method in class org.deeplearning4j.clustering.ClusterSet
addRow(List<String>) - Method in class org.deeplearning4j.util.StringGrid
addRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
addToConfusion(int, int) - Method in class org.deeplearning4j.eval.Evaluation: Adds to the confusion matrix
addVariable(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
adjustedrSquared(double, int, int) - Static method in class org.deeplearning4j.util.MathUtils: This calculates the adjusted r^2 including degrees of freedom.
AggregatePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Aggregate output pre processor
AggregatePreProcessor(OutputPreProcessor[]) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.AggregatePreProcessor
allMatches(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
allowEmptyClusters - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
ancestor(int, Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns the ancestor of the given tree
appendTo(String, File) - Static method in class org.deeplearning4j.util.FileOperations
appendToEach(String, int) - Method in class org.deeplearning4j.util.StringGrid
applyClusteringStrategy() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
applyDropConnectIfNecessary(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Applies drop connect relative to connections.
applyDropOutIfNecessary(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
applyOptimization(OptimisationStrategy, ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
applySparsity - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
applySparsity(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
applyTo(List<Point>) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
applyTo(List<Point>) - Method in interface org.deeplearning4j.clustering.algorithm.ClusteringAlgorithm
applyTo(List<INDArray>) - Method in interface org.deeplearning4j.clustering.ClusteringAlgorithm
approxEquals(Counter<E>, double) - Method in class org.deeplearning4j.berkeley.Counter
approxExp(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
approxLog(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
approxPow(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
ArchiveUtils - Class in org.deeplearning4j.util
ArchiveUtils() - Constructor for class org.deeplearning4j.util.ArchiveUtils
argMax() - Method in class org.deeplearning4j.berkeley.Counter: Finds the key with maximum count.
argMax() - Method in class org.deeplearning4j.berkeley.CounterMap: Finds the key with maximum count.
argsToMap(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils: Parses command line arguments into a Map.
argsToMap(String[], Map<String, Integer>) - Static method in class org.deeplearning4j.berkeley.StringUtils: Parses command line arguments into a Map.
argsToProperties(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
argsToProperties(String[], Map) - Static method in class org.deeplearning4j.berkeley.StringUtils: Analagous to StringUtils.argsToMap(java.lang.String[]).
arrayToString(String[]) - Static method in class org.deeplearning4j.util.StringUtils: Given an array of strings, return a comma-separated list of its elements.
asciify(String) - Method in class org.deeplearning4j.util.FingerPrintKeyer
asCounter() - Method in class org.deeplearning4j.berkeley.PriorityQueue: Returns a counter whose keys are the elements in this priority queue, and whose counts are the priorities in this queue.
asImageMiniBatches(File, int, int) - Method in class org.deeplearning4j.util.ImageLoader: Slices up an image in to a mini batch.
asMatrix(File) - Method in class org.deeplearning4j.util.ImageLoader
asMinPriorityQueue() - Method in class org.deeplearning4j.berkeley.Counter: Warning: all priorities are the negative of their counts in the counter here
asPriorityQueue() - Method in class org.deeplearning4j.berkeley.Counter: Builds a priority queue whose elements are the counter's elements, and whose priorities are those elements' counts in the counter.
asRowVector(File) - Method in class org.deeplearning4j.util.ImageLoader
assign(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
assign(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
AutoEncoder - Class in org.deeplearning4j.nn.conf.layers: Autoencoder.
AutoEncoder() - Constructor for class org.deeplearning4j.nn.conf.layers.AutoEncoder
AutoEncoder - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder: Autoencoder.
AutoEncoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
AutoEncoder(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder

B

backPropGradient2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Do a back prop iteration.
backPropGradientR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Do a back prop iteration.
BackTrackLineSearch - Class in org.deeplearning4j.optimize.solvers
BackTrackLineSearch(Model, StepFunction, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
BackTrackLineSearch(Model, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
backWard(Gradient, Gradient, INDArray, String) - Method in interface org.deeplearning4j.nn.api.Layer: Propagate errors backwards for a particular layer.
backward - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
backward - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
backward(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder: Whether to do back prop or not
backward(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
backWard(Gradient, Gradient, INDArray, String) - Method in class org.deeplearning4j.nn.layers.BaseLayer
backWard(Gradient, Gradient, INDArray, String) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
backWard(Gradient, Gradient, INDArray, String) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
backWard(Gradient, Gradient, INDArray, String) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
backward(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM: Back propagation in the given input
backwardGradient(INDArray, Gradient) - Method in interface org.deeplearning4j.nn.api.Layer: Calculate the gradient relative to the error in the next layer
backwardGradient(INDArray, Gradient) - Method in class org.deeplearning4j.nn.layers.BaseLayer
backwardGradient(INDArray, Gradient) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
backwardGradient(INDArray, Gradient) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
BarnesHutTsne - Class in org.deeplearning4j.plot: Barnes hut algorithm for TSNE, uses a dual tree approximation approach.
BarnesHutTsne(INDArray, INDArray, int, double, double, int, int, int, double, double, double) - Constructor for class org.deeplearning4j.plot.BarnesHutTsne
BarnesHutTsne.Builder - Class in org.deeplearning4j.plot
BaseClusteringAlgorithm - Class in org.deeplearning4j.clustering.algorithm: adapted to ndarray matrices
BaseClusteringAlgorithm(ClusteringStrategy) - Constructor for class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
BaseClusteringStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
BaseClusteringStrategy(ClusteringStrategyType, Integer, String, boolean) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
BaseDataFetcher - Class in org.deeplearning4j.datasets.fetchers: A base class for assisting with creation of matrices with the data applyTransformToDestination fetcher
BaseDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
BaseDatasetIterator - Class in org.deeplearning4j.datasets.iterator: Baseline implementation includes control over the data fetcher and some basic getters for metadata
BaseDatasetIterator(int, int, DataSetFetcher) - Constructor for class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
BaseLayer - Class in org.deeplearning4j.nn.layers: A layer with a bias and activation function
BaseLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
BaseLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
BaseOptimizer - Class in org.deeplearning4j.optimize.solvers: Base optimizer
BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
BasePretrainNetwork - Class in org.deeplearning4j.nn.conf.layers
BasePretrainNetwork() - Constructor for class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
BasePretrainNetwork - Class in org.deeplearning4j.nn.layers: Baseline class for any Neural Network used as a layer in a deep network *
BasePretrainNetwork(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
BasePretrainNetwork(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
batch() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
batch - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
batch() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
batch() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
batch() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Batch size
batch() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Batch size
batch() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
batch() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
batchSize() - Method in interface org.deeplearning4j.nn.api.Model: The current inputs batch size
batchSize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
batchSize(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
batchSize() - Method in class org.deeplearning4j.nn.layers.BaseLayer
batchSize() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
batchSize() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
batchSize() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
batchSize() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
batchSize() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: The batch size for the optimizer
batchSize() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
batchSize() - Method in class org.deeplearning4j.plot.BarnesHutTsne
bernoullis(double, double, double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the bernoulli trial for the given event.
BIAS - Static variable in class org.deeplearning4j.nn.params.RecursiveParamInitializer
BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.DefaultParamInitializer
binarize(int) - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer: Binarize the data based on the threshold (anything < threshold is zero) This is used for making the image brightness agnostic.
binarize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer: Binarize the data based on the threshold (anything < threshold is zero) This is used for making the image brightness agnostic.
binomial(RandomGenerator, int, double) - Static method in class org.deeplearning4j.util.MathUtils: Generates a binomial distributed number using the given rng
BinomialDistribution - Class in org.deeplearning4j.nn.conf.distribution: A binomial distribution.
BinomialDistribution(int, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.BinomialDistribution: Create a distribution
BinomialSamplingPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Binomial sampling pre processor
BinomialSamplingPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
broadcast(int...) - Method in class org.deeplearning4j.clustering.cluster.Point
build() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
build() - Method in class org.deeplearning4j.optimize.Solver.Builder
build() - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
build() - Method in class org.deeplearning4j.plot.Tsne.Builder
buildCounter(MapFactory<V, Double>) - Method in class org.deeplearning4j.berkeley.CounterMap
Builder() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
Builder() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
Builder() - Constructor for class org.deeplearning4j.optimize.Solver.Builder
Builder() - Constructor for class org.deeplearning4j.plot.BarnesHutTsne.Builder
Builder() - Constructor for class org.deeplearning4j.plot.Tsne.Builder
buildFromData(List<DataPoint>) - Static method in class org.deeplearning4j.clustering.vptree.VPTree
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.HashMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.WeakHashMapFactory
byteDesc(long) - Static method in class org.deeplearning4j.util.StringUtils: Return an abbreviated English-language desc of the byte length
byteToHexString(byte[], int, int) - Static method in class org.deeplearning4j.util.StringUtils: Given an array of bytes it will convert the bytes to a hex string representation of the bytes
byteToHexString(byte[]) - Static method in class org.deeplearning4j.util.StringUtils: Same as byteToHexString(bytes, 0, bytes.length).
ByteUtil - Class in org.deeplearning4j.util
ByteUtil() - Constructor for class org.deeplearning4j.util.ByteUtil

C

C - Static variable in class org.deeplearning4j.nn.params.RecursiveParamInitializer
calcGradient(Gradient, INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Calculate the gradient
calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
calculate(INDArray, int, double) - Method in class org.deeplearning4j.plot.Tsne
call(I) - Method in interface org.deeplearning4j.berkeley.MyMethod
capitalize(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Uppercases the first character of a string.
Cell - Class in org.deeplearning4j.clustering.quadtree: A cell representing a bounding box forthe quad tree
Cell(double, double, double, double) - Constructor for class org.deeplearning4j.clustering.quadtree.Cell
Cell - Class in org.deeplearning4j.clustering.sptree
Cell(int) - Constructor for class org.deeplearning4j.clustering.sptree.Cell
cgBackTrack(List<INDArray>, INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree: Iterate through the current list of gradients and backtrack upon an optimal step that improves the current score
checkDimensions(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
children() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
chiSquare2by2(int, int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Find a 2x2 chi-square value.
choleskyFromMatrix(RealMatrix) - Method in class org.deeplearning4j.util.MathUtils: This will return the cholesky decomposition of the given matrix
clamp(int, int, int) - Static method in class org.deeplearning4j.util.MathUtils: Clamps the value to a discrete value
CLASS - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
classCount(int) - Method in class org.deeplearning4j.eval.Evaluation: Returns the number of times the given label has actually occurred
Classifier - Interface in org.deeplearning4j.nn.api: A classifier (this is for supervised learning)
classifier() - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
ClassifierOverride - Class in org.deeplearning4j.nn.conf.override: Classifier over ride
ClassifierOverride(int) - Constructor for class org.deeplearning4j.nn.conf.override.ClassifierOverride
classify(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
classify(INDArray, Class<? extends Accumulation>) - Method in class org.deeplearning4j.clustering.ClusterSet
classifyPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
classifyPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
classifyPoint(ClusterSet, Point) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
classifyPoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
classifyPoints(List<Point>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
classifyPoints(List<Point>, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
classifyPoints(ClusterSet, List<Point>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
cleanup() - Method in class org.deeplearning4j.clustering.cluster.Point
clear() - Method in class org.deeplearning4j.berkeley.Counter
clear() - Method in interface org.deeplearning4j.nn.api.Model: Clear input
clear() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
clear() - Method in interface org.deeplearning4j.nn.gradient.Gradient: Clear residual parameters (useful for returning a gradient and then clearing old objects)
clear() - Method in class org.deeplearning4j.nn.layers.BaseLayer
clear() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
clear() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
clear() - Method in class org.deeplearning4j.nn.layers.OutputLayer
clear() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
clear() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Clear the inputs
clear() - Method in class org.deeplearning4j.plot.BarnesHutTsne
clear() - Method in class org.deeplearning4j.util.DiskBasedQueue
clear() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Removes all of the mappings from this map (optional operation).
clear() - Method in class org.deeplearning4j.util.MultiDimensionalSet: Removes all of the elements from this applyTransformToDestination (optional operation).
clone() - Method in class org.deeplearning4j.berkeley.PriorityQueue: Returns a clone of this priority queue.
clone() - Method in interface org.deeplearning4j.nn.api.Layer: Clone the layer
clone() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Creates and returns a copy of this object.
clone() - Method in class org.deeplearning4j.nn.layers.BaseLayer
clone() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
clone() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
clone() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
clone() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
close() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
close() - Method in class org.deeplearning4j.plot.FilterRenderer
Cluster - Class in org.deeplearning4j.clustering
Cluster() - Constructor for class org.deeplearning4j.clustering.Cluster
Cluster(String) - Constructor for class org.deeplearning4j.clustering.Cluster
Cluster(INDArray) - Constructor for class org.deeplearning4j.clustering.Cluster
Cluster(String, INDArray) - Constructor for class org.deeplearning4j.clustering.Cluster
Cluster(INDArray, List<INDArray>) - Constructor for class org.deeplearning4j.clustering.Cluster
Cluster - Class in org.deeplearning4j.clustering.cluster
Cluster() - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
Cluster(Point, String) - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
clusterColumn(int) - Method in class org.deeplearning4j.util.StringGrid
ClusterInfo - Class in org.deeplearning4j.clustering.cluster.info
ClusterInfo() - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterInfo
ClusterInfo(boolean) - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterInfo
ClusteringAlgorithm - Interface in org.deeplearning4j.clustering.algorithm
ClusteringAlgorithm - Interface in org.deeplearning4j.clustering
ClusteringAlgorithmCondition - Interface in org.deeplearning4j.clustering.algorithm.condition
ClusteringOptimization - Class in org.deeplearning4j.clustering.algorithm.optimisation
ClusteringOptimization(ClusteringOptimizationType, double) - Constructor for class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
ClusteringOptimizationType - Enum in org.deeplearning4j.clustering.algorithm.optimisation
ClusteringStrategy - Interface in org.deeplearning4j.clustering.algorithm.strategy
ClusteringStrategyType - Enum in org.deeplearning4j.clustering.algorithm.strategy
ClusterSet - Class in org.deeplearning4j.clustering.cluster
ClusterSet() - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
ClusterSet(String) - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
ClusterSet - Class in org.deeplearning4j.clustering
ClusterSet() - Constructor for class org.deeplearning4j.clustering.ClusterSet
ClusterSet(INDArray) - Constructor for class org.deeplearning4j.clustering.ClusterSet
ClusterSet(Class<? extends Accumulation>) - Constructor for class org.deeplearning4j.clustering.ClusterSet
ClusterSetInfo - Class in org.deeplearning4j.clustering.cluster.info
ClusterSetInfo() - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
ClusterSetInfo(boolean) - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
ClusterUtils - Class in org.deeplearning4j.clustering.cluster: Basic cluster utilities
ClusterUtils() - Constructor for class org.deeplearning4j.clustering.cluster.ClusterUtils
columns() - Method in class org.deeplearning4j.clustering.cluster.Point
combination(double, double) - Static method in class org.deeplearning4j.util.MathUtils: This returns the combination of n choose r
combineColumns(int, Integer[]) - Method in class org.deeplearning4j.util.StringGrid: Combine the column based on a template and a number of template variable columns.
combineColumns(int, int[]) - Method in class org.deeplearning4j.util.StringGrid: Combine the column based on a template and a number of template variable columns.
COMMA - Static variable in class org.deeplearning4j.util.StringUtils
compare(Pair<F, S>, Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair.DefaultLexicographicPairComparator
compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.FirstComparator
compare(Pair<F, S>, Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair.LexicographicPairComparator
compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.SecondComparator
compare(Map<String, Integer>, Map<String, Integer>) - Method in class org.deeplearning4j.util.StringCluster.SizeComparator
compareTo(Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair: Compares this object with the specified object for order.
compareTo(HeapItem) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
ComposableInputPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Composable input pre processor
ComposableInputPreProcessor(InputPreProcessor...) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
ComposableIterationListener - Class in org.deeplearning4j.optimize.listeners: A group of listeners
ComposableIterationListener(IterationListener...) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
ComposableIterationListener(Collection<IterationListener>) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
ComposableOutputPostProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Composable output post processor
ComposableOutputPostProcessor(OutputPreProcessor...) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ComposableOutputPostProcessor
ComposableOverride - Class in org.deeplearning4j.nn.conf.override: Configuration override
ComposableOverride(ConfOverride...) - Constructor for class org.deeplearning4j.nn.conf.override.ComposableOverride
computeClusterInfos(Cluster, String) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
computeClusterSetInfo(ClusterSet) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
computeClusterSetInfo(ClusterSet, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
computeDeltas2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
computeDeltasR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.sptree.SpTree: Compute edge forces using barns hut
computeGaussianKernel(INDArray, double, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne: Computes a gaussian kernel given a vector of squared distance distances
computeGaussianPerplexity(INDArray, double) - Method in class org.deeplearning4j.plot.BarnesHutTsne: Convert data to probability co-occurrences (aka calculating the kernel)
computeGaussianPerplexity(INDArray, double) - Method in class org.deeplearning4j.plot.Tsne: Convert data to probability co-occurrences (aka calculating the kernel)
computeHistogramBucketIndex(double, double, double, int) - Method in class org.deeplearning4j.plot.FilterRenderer
computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Compute non edge forces using barnes hut
computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.sptree.SpTree: Compute non edge forces using barnes hut
computeSquareDistancesFromNearestCluster(ClusterSet, List<Point>, INDArray, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
concat(Iterable<Iterator<? extends T>>) - Static method in class org.deeplearning4j.berkeley.Iterators
concat(Iterator<? extends T>...) - Static method in class org.deeplearning4j.berkeley.Iterators
concat(Iterable<T>, Iterable<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
concurrentSkipListSet() - Static method in class org.deeplearning4j.util.MultiDimensionalSet
cond(Condition) - Method in class org.deeplearning4j.clustering.cluster.Point
condi(Condition) - Method in class org.deeplearning4j.clustering.cluster.Point
conf() - Method in interface org.deeplearning4j.nn.api.Model: The configuration for the neural network
conf - Variable in class org.deeplearning4j.nn.layers.BaseLayer
conf() - Method in class org.deeplearning4j.nn.layers.BaseLayer
conf() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
conf() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
conf() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
conf - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
conf() - Method in class org.deeplearning4j.plot.BarnesHutTsne
configure(NeuralNetConfiguration) - Method in class org.deeplearning4j.optimize.Solver.Builder
ConfOverride - Interface in org.deeplearning4j.nn.conf.override: Interface for a function to overrideLayer builder configurations at a particular layer
confOverrides - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
confs(List<NeuralNetConfiguration>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
ConfusionMatrix<T extends Comparable<? super T>> - Class in org.deeplearning4j.eval
ConfusionMatrix() - Constructor for class org.deeplearning4j.eval.ConfusionMatrix: Creates an empty confusion Matrix
ConfusionMatrix(ConfusionMatrix<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix: Creates a new ConfusionMatrix initialized with the contents of another ConfusionMatrix.
conjGradient(INDArray, INDArray, INDArray, int) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
ConjugateGradient - Class in org.deeplearning4j.optimize.solvers: Modified based on cc.mallet.optimize.ConjugateGradient
no termination when zero tolerance
ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
connect(List<Tree>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Connects the given trees and sets the parents of the children
constrainGradientToUnitNorm(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
constrainGradientToUnitNorm - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
contains(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
contains(double) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
contains(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
contains(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
contains(K, T) - Method in class org.deeplearning4j.util.MultiDimensionalMap
contains(Object) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns true if this applyTransformToDestination contains the specified element.
contains(K, V) - Method in class org.deeplearning4j.util.MultiDimensionalSet
containsAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
containsAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns true if this applyTransformToDestination contains all of the elements of the specified collection.
containsKey(E) - Method in class org.deeplearning4j.berkeley.Counter: Returns whether the counter contains the given key.
containsKey(K) - Method in class org.deeplearning4j.berkeley.CounterMap
containsKey(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns true if this map contains a mapping for the specified key.
containsPoint(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.Cell: Whether the given point is contained within this cell
containsValue(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns true if this map maps one or more keys to the specified value.
contrastiveDivergence() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Contrastive divergence revolves around the idea of approximating the log likelihood around x1(input) with repeated sampling.
ConvergenceCondition - Class in org.deeplearning4j.clustering.algorithm.condition
ConvergenceCondition(Condition, double) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.ConvergenceCondition
convertListPairs(List<DataSet>) - Method in class org.deeplearning4j.base.LFWLoader
ConvexOptimizer - Interface in org.deeplearning4j.optimize.api: Convex optimizer.
CONVOLUTION_BIAS - Static variable in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
CONVOLUTION_WEIGHTS - Static variable in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
ConvolutionDownSampleLayer - Class in org.deeplearning4j.nn.conf.layers: Convolutional and pooling layer
ConvolutionDownSampleLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer
ConvolutionDownSampleLayer - Class in org.deeplearning4j.nn.layers.convolution: Convolutional and pooling layer
ConvolutionDownSampleLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer: Create a layer from a configuration
ConvolutionDownSampleLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
ConvolutionDownSampleLayer.ConvolutionType - Enum in org.deeplearning4j.nn.conf.layers: Convolution type: max avg or sum
ConvolutionInputPreProcessor - Class in org.deeplearning4j.nn.layers.convolution.preprocessor: A convolution input pre processor.
ConvolutionInputPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.layers.convolution.preprocessor.ConvolutionInputPreProcessor
ConvolutionLayer - Class in org.deeplearning4j.nn.conf.layers
ConvolutionLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
ConvolutionLayer - Class in org.deeplearning4j.nn.layers.convolution: Convolution layer
ConvolutionLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
ConvolutionLayerFactory - Class in org.deeplearning4j.nn.layers.factory: Create a convolution layer
ConvolutionLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.ConvolutionLayerFactory
ConvolutionParamInitializer - Class in org.deeplearning4j.nn.params: Initialize convolution params.
ConvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.ConvolutionParamInitializer
ConvolutionPostProcessor - Class in org.deeplearning4j.nn.layers.convolution.preprocessor: Used for feeding the output of a conv net in to a 2d classifier.
ConvolutionPostProcessor(int[]) - Constructor for class org.deeplearning4j.nn.layers.convolution.preprocessor.ConvolutionPostProcessor
ConvolutionPostProcessor() - Constructor for class org.deeplearning4j.nn.layers.convolution.preprocessor.ConvolutionPostProcessor
convolutionType(ConvolutionDownSampleLayer.ConvolutionType) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
convolutionType - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
ConvolutionUtils - Class in org.deeplearning4j.util: Convolutional shape utilities
ConvolutionUtils() - Constructor for class org.deeplearning4j.util.ConvolutionUtils
coordSplit(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the coordinate split in a list of coordinates such that the values for ret[0] are the x values and ret[1] are the y values
coordSplit(List<Double>) - Static method in class org.deeplearning4j.util.MathUtils: This returns the coordinate split in a list of coordinates such that the values for ret[0] are the x values and ret[1] are the y values
corner(int) - Method in class org.deeplearning4j.clustering.sptree.Cell
corner() - Method in class org.deeplearning4j.clustering.sptree.Cell
correlation(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: Returns the correlation coefficient of two double vectors.
corruptionLevel(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
corruptionLevel - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
count(V, V) - Method in interface org.deeplearning4j.berkeley.CounterMap.CountFunction
Counter<E> - Class in org.deeplearning4j.berkeley: A map from objects to doubles.
Counter() - Constructor for class org.deeplearning4j.berkeley.Counter
Counter(boolean) - Constructor for class org.deeplearning4j.berkeley.Counter
Counter(MapFactory<E, Double>) - Constructor for class org.deeplearning4j.berkeley.Counter
Counter(Map<? extends E, Double>) - Constructor for class org.deeplearning4j.berkeley.Counter
Counter(Counter<? extends E>) - Constructor for class org.deeplearning4j.berkeley.Counter
Counter(Collection<? extends E>) - Constructor for class org.deeplearning4j.berkeley.Counter
CounterMap<K,V> - Class in org.deeplearning4j.berkeley: Maintains counts of (key, value) pairs.
CounterMap(CounterMap<K, V>) - Constructor for class org.deeplearning4j.berkeley.CounterMap
CounterMap() - Constructor for class org.deeplearning4j.berkeley.CounterMap
CounterMap(MapFactory<K, Counter<V>>, MapFactory<V, Double>) - Constructor for class org.deeplearning4j.berkeley.CounterMap
CounterMap(boolean) - Constructor for class org.deeplearning4j.berkeley.CounterMap
CounterMap.CountFunction<V> - Interface in org.deeplearning4j.berkeley
create() - Method in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory: Create a dataset iterator
create(NeuralNetConfiguration, int, int, Collection<IterationListener>) - Method in interface org.deeplearning4j.nn.api.LayerFactory: Create a layer based on the based in configuration and an added context.
create(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.LayerFactory: Create a layer based on the based in configuration
create(NeuralNetConfiguration, Collection<IterationListener>) - Method in interface org.deeplearning4j.nn.api.LayerFactory: Create a layer based on the based in configuration
create(NeuralNetConfiguration, int, int, Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
create(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
create(NeuralNetConfiguration, Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
createAppendingOutputStream(File) - Static method in class org.deeplearning4j.util.FileOperations
createBias(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
createBias(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
createDistribution(Distribution) - Static method in class org.deeplearning4j.nn.conf.distribution.Distributions
createGradient(INDArray...) - Method in class org.deeplearning4j.nn.layers.BaseLayer: Create a gradient list based on the passed in parameters.
createGradient(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
createInputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher: Creates a feature vector
createOutputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
createOutputVector(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher: Creates an output label matrix
createRandom(Random) - Static method in class org.deeplearning4j.nn.conf.rng.Randoms: Static method for instantiating an nd4j random number generator from a configuration object.
createStepFunction(StepFunction) - Static method in class org.deeplearning4j.optimize.stepfunctions.StepFunctions
createWeightMatrix(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
createWeightMatrix(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
CSVDataFetcher - Class in org.deeplearning4j.datasets.fetchers: CSV record based data fetcher
CSVDataFetcher(InputStream, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher: Constructs a csv data fetcher with the specified label column skipping no lines
CSVDataFetcher(File, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher: Constructs a csv data fetcher with the specified label column skipping no lines
CSVDataFetcher(InputStream, int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher: Constructs a csv data fetcher with the specified number of lines to skip
CSVDataFetcher(File, int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher: Constructs a csv data fetcher with the specified number of lines to skip
CSVDataSetIterator - Class in org.deeplearning4j.datasets.iterator: CSVDataSetIterator CSV reader for a dataset file
CSVDataSetIterator(int, int, InputStream, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
CSVDataSetIterator(int, int, File, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
CSVDataSetIterator(int, int, InputStream, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
CSVDataSetIterator(int, int, File, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
cumsum(int) - Method in class org.deeplearning4j.clustering.cluster.Point
cumsumi(int) - Method in class org.deeplearning4j.clustering.cluster.Point
curr - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
cursor() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
cursor - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
cursor() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
cursor() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
cursor() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Direct access to a number represenative of iterating through a dataset
cursor() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
cursor() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: The current cursor if applicable
cursor() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: The current cursor if applicable
cursor() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
cursor() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
CURVES_FILE_NAME - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
CURVES_URL - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
CurvesDataFetcher - Class in org.deeplearning4j.datasets.fetchers: Curves data fetcher
CurvesDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
CurvesDataSetIterator - Class in org.deeplearning4j.datasets.iterator: Curves data applyTransformToDestination iterator
CurvesDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CurvesDataSetIterator

D

dampingFactor - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
dampingFactor(double) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
dampingFactor - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
dampingUpdate(double, double, double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
data() - Method in class org.deeplearning4j.clustering.cluster.Point
DataPoint - Class in org.deeplearning4j.clustering.sptree: A vector with an index and function for distance
DataPoint(int, INDArray, boolean) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
DataPoint(int, INDArray, String, boolean) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
DataPoint(int, INDArray) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
DataPoint(int, INDArray, String) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
DataSetFetcher - Interface in org.deeplearning4j.datasets.iterator: A low level interface for loading datasets in to memory.
DataSetIterator - Interface in org.deeplearning4j.datasets.iterator: A DataSetIterator handles traversing through a dataset and preparing data for a neural network.
DataSetIteratorFactory - Interface in org.deeplearning4j.datasets.creator: Base interface for creating datasetiterators
DataSetPreProcessor - Interface in org.deeplearning4j.datasets.iterator: Pre process a dataset
DataSets - Class in org.deeplearning4j.datasets
DataSets() - Constructor for class org.deeplearning4j.datasets.DataSets
decode(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
decode(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
decode(INDArray) - Method in class org.deeplearning4j.util.Viterbi: Decodes the given labels, assuming its a binary label matrix
decode(INDArray, boolean) - Method in class org.deeplearning4j.util.Viterbi: Decodes a series of labels
DECODER_BIAS - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
DECODER_WEIGHTS - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
dedupeByCluster(int) - Method in class org.deeplearning4j.util.StringGrid: Deduplicate based on the column clustering signature
dedupeByClusterAll() - Method in class org.deeplearning4j.util.StringGrid
DeepLearningConfigurable - Interface in org.deeplearning4j.nn.conf
DeepLearningException - Exception in org.deeplearning4j.exception
DeepLearningException() - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningIOUtil - Class in org.deeplearning4j.util
DeepLearningIOUtil() - Constructor for class org.deeplearning4j.util.DeepLearningIOUtil
defaultConfiguration - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
DefaultFactory(Class) - Constructor for class org.deeplearning4j.berkeley.Factory.DefaultFactory
DefaultGradient - Class in org.deeplearning4j.nn.gradient: Default gradient implementation.
DefaultGradient() - Constructor for class org.deeplearning4j.nn.gradient.DefaultGradient
defaultIterationCount - Static variable in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
defaultIterationCount - Static variable in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
DefaultLayerFactory - Class in org.deeplearning4j.nn.layers.factory: Default layer factory: create a bias and a weight matrix
DefaultLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
DefaultLexicographicPairComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.DefaultLexicographicPairComparator
DefaultParamInitializer - Class in org.deeplearning4j.nn.params: Static weight initializer with just a weight matrix and a bias
DefaultParamInitializer() - Constructor for class org.deeplearning4j.nn.params.DefaultParamInitializer
DefaultRandom - Class in org.deeplearning4j.nn.conf.rng
DefaultRandom() - Constructor for class org.deeplearning4j.nn.conf.rng.DefaultRandom: Initialize with a seed based on the current time.
DefaultRandom(long) - Constructor for class org.deeplearning4j.nn.conf.rng.DefaultRandom: Initialize with the given seed.
DefaultStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions: Default step function
DefaultStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
DefaultStepFunction - Class in org.deeplearning4j.optimize.stepfunctions: Default step function
DefaultStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
delete(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
depth() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: The depth of the node
depth() - Method in class org.deeplearning4j.clustering.sptree.SpTree: The depth of the node
depth() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Finds the depth of the tree.
depth(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns the distance between this node and the specified subnode
derivativeActivation(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Take the derivative of the given input based on the activation
derivativeActivation(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
derivativeActivation(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
derivativeActivation(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
deriveClusterInfoDistanceStatistics(ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.deserializers.PreProcessorDeSerializer
determinationCoefficient(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils: This returns the determination coefficient of two vectors given a length
difference(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
difference(Collection<? extends T>, Collection<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils: Return is s1 \ s2
dimShuffle(Object[], int[], boolean[]) - Method in class org.deeplearning4j.clustering.cluster.Point
discretize(double, double, double, int) - Static method in class org.deeplearning4j.util.MathUtils: Discretize the given value
DiskBasedQueue<E> - Class in org.deeplearning4j.util: Naive disk based queue for storing items on disk.
DiskBasedQueue() - Constructor for class org.deeplearning4j.util.DiskBasedQueue
DiskBasedQueue(String) - Constructor for class org.deeplearning4j.util.DiskBasedQueue
DiskBasedQueue(File) - Constructor for class org.deeplearning4j.util.DiskBasedQueue
dist(Distribution) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
dist - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
distance(DataPoint) - Method in class org.deeplearning4j.clustering.sptree.DataPoint: Euclidean distance
distance1(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
distance2(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
distanceFinderZValue(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This will translate a vector in to an equivalent integer
distanceFunction - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
Distribution - Class in org.deeplearning4j.nn.conf.distribution: An abstract distribution.
Distribution() - Constructor for class org.deeplearning4j.nn.conf.distribution.Distribution
Distributions - Class in org.deeplearning4j.nn.conf.distribution: Static method for instantiating an nd4j distribution from a configuration object.
Distributions() - Constructor for class org.deeplearning4j.nn.conf.distribution.Distributions
distributionVariationRateLessThan(double) - Static method in class org.deeplearning4j.clustering.algorithm.condition.ConvergenceCondition
div(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
div(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
div(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
div(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
div(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
div(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
divi(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
diviColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
diviRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
divRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
Dl4jReflection - Class in org.deeplearning4j.util
doBackWard(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
dotProduct(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
downloadAndUntar() - Method in class org.deeplearning4j.base.MnistFetcher
draw() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
draw() - Method in class org.deeplearning4j.plot.FilterRenderer
draw() - Method in class org.deeplearning4j.plot.MultiLayerNetworkReconstructionRender
draw() - Method in class org.deeplearning4j.plot.NeuralNetworkReconstructionRender
DrawReconstruction - Class in org.deeplearning4j.datasets.mnist.draw
DrawReconstruction(INDArray, int, int) - Constructor for class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
DrawReconstruction(INDArray) - Constructor for class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
dropOut(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
dropOut - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
dropoutMask - Variable in class org.deeplearning4j.nn.layers.BaseLayer
dup() - Method in class org.deeplearning4j.clustering.cluster.Point

E

editDistance(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Computes the Levenshtein (edit) distance of the two given Strings.
element() - Method in class org.deeplearning4j.clustering.cluster.Point
element() - Method in class org.deeplearning4j.util.DiskBasedQueue
emptyIterator() - Static method in class org.deeplearning4j.berkeley.Iterators
emptyStringArray - Static variable in class org.deeplearning4j.util.StringUtils
encode(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
endsForSlices() - Method in class org.deeplearning4j.clustering.cluster.Point
endWhenDistributionVariationRateLessThan(double) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
endWhenDistributionVariationRateLessThan(double) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
endWhenIterationCountEquals(int) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
endWhenIterationCountEquals(int) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
enlarge(double) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
enlargeTo(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
ensureCounter(K) - Method in class org.deeplearning4j.berkeley.CounterMap
entropy(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the entropy (information gain, or uncertainty of a random variable).
Entry(K, T, V) - Constructor for class org.deeplearning4j.util.MultiDimensionalMap.Entry
entrySet() - Method in class org.deeplearning4j.berkeley.Counter
entrySet() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns a Set view of the mappings contained in this map.
EnumUtil - Class in org.deeplearning4j.util: Created by agibsonccc on 9/3/14.
EnumUtil() - Constructor for class org.deeplearning4j.util.EnumUtil
eps(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
eps(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
epsi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
epsi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
EpsTermination - Class in org.deeplearning4j.optimize.terminations: Epsilon termination (absolute change based on tolerance)
EpsTermination(double, double) - Constructor for class org.deeplearning4j.optimize.terminations.EpsTermination
EpsTermination() - Constructor for class org.deeplearning4j.optimize.terminations.EpsTermination
eq(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
eq(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
eqi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
eqi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
equals(Object) - Method in class org.deeplearning4j.berkeley.Counter
equals(Object) - Method in class org.deeplearning4j.berkeley.Pair
equals(Object) - Method in class org.deeplearning4j.berkeley.Triple
equals(Object) - Method in class org.deeplearning4j.clustering.quadtree.Cell
equals(Object) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
equals(Object) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
equals(Object) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.LSTM
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.RBM
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder
equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
equals(Object) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
equals(Object) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
equals(Object) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
equals(Object) - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
equals(Object) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
equals(Object) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
equals(Object) - Method in class org.deeplearning4j.util.Index
equals(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap
error(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Calculate error with respect to the current layer.
error(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
error(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
error(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
error() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns the prediction error for this node
errorFor(double, double) - Static method in class org.deeplearning4j.util.MathUtils
errorSignal(Gradient, INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Error signal for this layer Using the amount of error caused by this layer calculate the error signal used as input in to the next layer.
errorSignal(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
errorSignal(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
errorSignal(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
errorSum() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns the total prediction error for this tree and its children
ESCAPE_CHAR - Static variable in class org.deeplearning4j.util.StringUtils
escapeHTML(String) - Static method in class org.deeplearning4j.util.StringUtils: Escapes HTML Special characters present in the string.
escapeString(String, char[], char) - Static method in class org.deeplearning4j.berkeley.StringUtils
escapeString(String) - Static method in class org.deeplearning4j.util.StringUtils: Escape commas in the string using the default escape char
escapeString(String, char, char) - Static method in class org.deeplearning4j.util.StringUtils: Escape charToEscape in the string with the escape char escapeChar
escapeString(String, char, char[]) - Static method in class org.deeplearning4j.util.StringUtils
euclideanDistance(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the distance distance of two vectors sum(i=1,n) (q_i - p_i)^2
euclideanDistance(float[], float[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the distance distance of two vectors sum(i=1,n) (q_i - p_i)^2
eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.Evaluation: Collects statistics on the real outcomes vs the guesses.
Evaluation - Class in org.deeplearning4j.eval: Evaluation metrics: precision, recall, f1
Evaluation() - Constructor for class org.deeplearning4j.eval.Evaluation
exactBinomial(int, int, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Find a one tailed exact binomial test probability.
exp(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath

F

f1() - Method in class org.deeplearning4j.eval.Evaluation: TP: true positive FP: False Positive FN: False Negative F1 score: 2 * TP / (2TP + FP + FN)
f1(int) - Method in class org.deeplearning4j.eval.Evaluation: Calculate f1 score for a given class
factorial(double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the factorial of the given number n.
Factory<T> - Interface in org.deeplearning4j.berkeley
Factory.DefaultFactory<T> - Class in org.deeplearning4j.berkeley
FACTORY_KEY - Static variable in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory
falsePositive() - Method in class org.deeplearning4j.eval.Evaluation: False positive: wrong guess
featureMapSize(int...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
feedForward() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForward(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForwardR(List<INDArray>, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Feed forward with the r operator
feedForwardR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Feed forward with the r operator
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.CSVDataFetcher: Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher: Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
fetch(int) - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher: Fetches the next dataset.
fetcher - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
fileNameClean(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns a "clean" version of the given filename in which spaces have been converted to dashes and all non-alphaneumeric chars are underscores.
FileOperations - Class in org.deeplearning4j.util
fillDown(String, int) - Method in class org.deeplearning4j.util.StringGrid
fillList(Iterator<? extends T>, List<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
fillList(Iterator<? extends T>) - Static method in class org.deeplearning4j.berkeley.Iterators
Filter<T> - Interface in org.deeplearning4j.berkeley: Filters are boolean cooccurrences which accept or reject items.
filter(Iterator<T>, Filter<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
filterBySimilarity(double, int, int) - Method in class org.deeplearning4j.util.StringGrid
FilteredIterator(Filter<T>, Iterator<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
FilteredIterator(Filter<T>, Iterable<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
FilterPanel - Class in org.deeplearning4j.plot
FilterPanel(BufferedImage) - Constructor for class org.deeplearning4j.plot.FilterPanel
FilterRenderer - Class in org.deeplearning4j.plot: Adapted from: https://github.com/jpatanooga/Metronome/blob/master/src/main/java/tv/floe/metronome/deeplearning/rbm/visualization/RBMRenderer.java
FilterRenderer() - Constructor for class org.deeplearning4j.plot.FilterRenderer
filterRowsByColumn(int, Collection<String>) - Method in class org.deeplearning4j.util.StringGrid
filterSize(int...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
finalMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
finalMomentum - Variable in class org.deeplearning4j.plot.Tsne
find(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Say whether this regular expression can be found inside this String.
findIndex(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Returns the cell of this element
findNext(String, char, char, int, StringBuilder) - Static method in class org.deeplearning4j.util.StringUtils: Finds the first occurrence of the separator character ignoring the escaped separators starting from the index.
finetune(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Run SGD based on the given labels
finetune(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Run SGD based on the given labels
FingerPrintKeyer - Class in org.deeplearning4j.util: Copied from google refine: takes the key and gets rid of all punctuation, transforms to lower case and alphabetic sorts the words
FingerPrintKeyer() - Constructor for class org.deeplearning4j.util.FingerPrintKeyer
firstChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
FirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.FirstComparator
fit(DataSetIterator) - Method in interface org.deeplearning4j.nn.api.Classifier
fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit(INDArray, int[]) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit() - Method in interface org.deeplearning4j.nn.api.Model: All models have a fit method
fit(INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Fit the model to the given data
fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
fit() - Method in class org.deeplearning4j.nn.layers.BaseLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
fit() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
fit() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
fit() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Note: k is the first input iken params.
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.OutputLayer
fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Fit the model
fit(DataSet) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Fit the model
fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Fit the model
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Fit the model to the given data
fit() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
fit(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
fit() - Method in class org.deeplearning4j.plot.BarnesHutTsne
fit(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
FixedClusterCountStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
FixedClusterCountStrategy(Integer, String, boolean) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
FixedIterationCountCondition - Class in org.deeplearning4j.clustering.algorithm.condition
FixedIterationCountCondition(int) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
flattenedImageFromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
formatPercent(double, int) - Static method in class org.deeplearning4j.util.StringUtils: Format a percentage for presentation to the user.
formatTime(long) - Static method in class org.deeplearning4j.util.StringUtils: Given the time in long milliseconds, returns a String in the format Xhrs, Ymins, Z sec.
formatTimeDiff(long, long) - Static method in class org.deeplearning4j.util.StringUtils: Given a finish and start time in long milliseconds, returns a String in the format Xhrs, Ymins, Z sec, for the time difference between two times.
forward(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM: Forward propagation
frame - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
frame - Variable in class org.deeplearning4j.plot.FilterRenderer
fromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
fromFile(String, String) - Static method in class org.deeplearning4j.util.StringGrid
fromImageFile(int, File) - Method in class org.deeplearning4j.base.LFWLoader
fromInput(InputStream, String) - Static method in class org.deeplearning4j.util.StringGrid
fromJson(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration: Create a neural net configuration from json
fromJson(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Create a neural net configuration from json
fromString(String, String) - Static method in class org.deeplearning4j.util.MathUtils: This will take a given string and separator and convert it to an equivalent double array.

G

gains - Variable in class org.deeplearning4j.plot.Tsne
generateHistogramBuckets(INDArray, int) - Method in class org.deeplearning4j.plot.FilterRenderer: Take some matrix input data and a bucket count and compute: - a list of N buckets, each with: 1.
generateUniform(int) - Static method in class org.deeplearning4j.util.MathUtils: This will generate a series of uniformally distributed numbers between l times
get(NDArrayIndex...) - Method in class org.deeplearning4j.clustering.cluster.Point
get(int) - Method in class org.deeplearning4j.util.Index
get(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns the value to which the specified key is mapped, or null if this map contains no mapping for the key.
get(K, T) - Method in class org.deeplearning4j.util.MultiDimensionalMap
getAccumulation() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getActivationFunction() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getActualTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Computes the total number of times the class actually appeared in the data.
getAdaGrad() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: The adagrad in this model
getAdaGrad() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
getAdaGradForVariable(String) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Get adagrad for a variable
getAdaGradForVariable(String) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
getAllImagesAsMatrix() - Method in class org.deeplearning4j.base.LFWLoader
getAllImagesAsMatrix(int) - Method in class org.deeplearning4j.base.LFWLoader
getAllWithSimilarity(double, int, int) - Method in class org.deeplearning4j.util.StringGrid
getArray() - Method in class org.deeplearning4j.clustering.cluster.Point
getAveragePointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getAveragePointDistanceFromClusterCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getBackPropGradient2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Gets the back prop gradient with the r operator (gauss vector) and the associated precon matrix This is also called computeGV
getBackPropRGradient(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Gets the back prop gradient with the r operator (gauss vector) This is also called computeGV
getBatchSize() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getBegin() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
getBoundary() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getBoundary() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getCenter() - Method in class org.deeplearning4j.clustering.cluster.Cluster
getCenter() - Method in class org.deeplearning4j.clustering.Cluster
getCenterOfMass() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getCenterOfMass() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getCenters() - Method in class org.deeplearning4j.clustering.ClusterSet
getChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getChildren() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
getClass(T) - Static method in class org.deeplearning4j.util.ReflectionUtils: Return the correctly-typed Class of the given object.
getClasses() - Method in class org.deeplearning4j.eval.ConfusionMatrix: Gives the applyTransformToDestination of all classes in the confusion matrix.
getCluster(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getCluster() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
getClusterCenter(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getClusterCenterId(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getClusterCount() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getClusterCount() - Method in class org.deeplearning4j.clustering.ClusterSet
getClusterInfo(String) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getClusteringOptimizationValue() - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
getClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getClusters() - Method in class org.deeplearning4j.clustering.ClusterSet
getClusters() - Method in class org.deeplearning4j.util.StringCluster
getClusterSetInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
getClustersInfos() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
getClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
getCols() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Number of columns per image.
getColumn(int) - Method in class org.deeplearning4j.clustering.cluster.Point
getColumn(int) - Method in class org.deeplearning4j.util.StringGrid
getColumns(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
getConf(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getConfs() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getConvolutionType() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: The convolution type to use with the convolution layer
getCorruptedInput(INDArray, double) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork: Corrupts the given input by doing a binomial sampling given the corruption level
getCorruptionLevel() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getCount(E) - Method in class org.deeplearning4j.berkeley.Counter: Get the count of the element, or zero if the element is not in the counter.
getCount(K, V) - Method in class org.deeplearning4j.berkeley.CounterMap: Gets the count of the given (key, value) entry, or zero if that entry is not present.
getCount(K) - Method in class org.deeplearning4j.berkeley.CounterMap: Gets the total count of the given key, or zero if that key is not present.
getCount() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
getCount(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Gives the count of the number of times the "predicted" class was predicted for the "actual" class.
getCounter(K) - Method in class org.deeplearning4j.berkeley.CounterMap: Gets the sub-counter for the given key.
getCounters() - Method in class org.deeplearning4j.berkeley.CounterMap
getCumSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getCumSize() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getCurrentIndex() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: The current entry index.
getD() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
getD() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getDampingFactor() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getDataFor(int) - Method in class org.deeplearning4j.base.LFWLoader
getDeflt() - Method in class org.deeplearning4j.berkeley.Counter
getDist() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getDistance(Point, Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getDistance() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
getDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
getDistanceFromNearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getDistanceFromNearestCluster(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
getDistanceFunction() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
getDistanceFunction() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
getDistanceFunction() - Method in class org.deeplearning4j.clustering.ClusterSet
getDistances() - Method in class org.deeplearning4j.clustering.vptree.VPTree
getDistancesBetweenClustersCenters() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getDistanceToCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
getDouble(int...) - Method in class org.deeplearning4j.clustering.cluster.Point
getDouble(int) - Method in class org.deeplearning4j.clustering.cluster.Point
getDouble(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
getDropOut() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getEmptyConstructor(Class<?>) - Static method in class org.deeplearning4j.util.Dl4jReflection: Gets the empty constructor from a class
getEnd() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: Number of bytes for each entry.
getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
getEntrySet() - Method in class org.deeplearning4j.berkeley.Counter
getEntrySet() - Method in class org.deeplearning4j.berkeley.CounterMap
getFactory(NeuralNetConfiguration) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories: Get the factory based on the passed in class
getFactory(Layer) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories: Get the factory based on the passed in class
getFeatureMapSize() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getFeatureMatrix(int) - Method in class org.deeplearning4j.base.LFWLoader: Get the first num found images
getFieldsAsProperties(Object, Class<?>[]) - Static method in class org.deeplearning4j.util.Dl4jReflection: Get fields as properties
getFilterSize() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getFirst() - Method in class org.deeplearning4j.berkeley.Pair
getFirst() - Method in class org.deeplearning4j.berkeley.Triple
getFirstKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
getFloat(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
getFloat(int) - Method in class org.deeplearning4j.clustering.cluster.Point
getFloat(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
getFormattedTimeWithDiff(DateFormat, long, long) - Static method in class org.deeplearning4j.util.StringUtils: Formats time in ms and appends difference (finishTime - startTime) as returned by formatTimeDiff().
getGradientFor(String) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
getGradientFor(String) - Method in interface org.deeplearning4j.nn.gradient.Gradient: The gradient for the given variable
getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
getHeadWord() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
getHeightAndWidth(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils: Get the height and width from the configuration
getHeightAndWidth(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils: Get the height and width for an image
getHh() - Method in class org.deeplearning4j.clustering.quadtree.Cell
getHiddenLayerSizes() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getHiddenUnit() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getHostname() - Static method in class org.deeplearning4j.util.StringUtils: Return hostname without throwing exception.
getHw() - Method in class org.deeplearning4j.clustering.quadtree.Cell
getId() - Method in class org.deeplearning4j.clustering.cluster.Cluster
getId() - Method in class org.deeplearning4j.clustering.cluster.Point
getIfNotExists() - Method in class org.deeplearning4j.base.LFWLoader
getImage() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
getImage() - Method in class org.deeplearning4j.plot.FilterRenderer
getImages(int, File) - Method in class org.deeplearning4j.base.LFWLoader
getImages() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Get the underlying images file as MnistImageFile.
getImagesAsList() - Method in class org.deeplearning4j.base.LFWLoader
getIndex() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
getIndex() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
getIndex() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
getIndex() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getIndex() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
getInitialClusterCount() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
getInitialClusterCount() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
getInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getInputPreProcess(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getInstance(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
getInt(int...) - Method in class org.deeplearning4j.clustering.cluster.Point
getItems() - Method in class org.deeplearning4j.clustering.vptree.VPTree
getIterationCount() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
getIterationInfo(int) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
getIterationListener() - Method in class org.deeplearning4j.plot.Tsne
getIterationListeners() - Method in interface org.deeplearning4j.nn.api.Layer: Get the iteration listeners for this layer.
getIterationListeners() - Method in class org.deeplearning4j.nn.layers.BaseLayer
getIterationListeners() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
getIterationListeners() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
getIterationsInfos() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
getK() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getKernel() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry: Returns the key corresponding to this entry.
getL1() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getL2() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getLabel() - Method in class org.deeplearning4j.clustering.cluster.Cluster
getLabel() - Method in class org.deeplearning4j.clustering.cluster.Point
getLabels() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Get the underlying labels file as MnistLabelFile.
getLabels() - Method in class org.deeplearning4j.nn.layers.OutputLayer
getLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getLayer() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getLayerWiseConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getLeaves() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Gets the leaves of the tree.
getLeaves(List<T>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Gets the leaves of the tree.
getLeft() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
getLeft() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
getListeners() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getLogMetaInstability() - Method in class org.deeplearning4j.util.Viterbi
getLogOfDiangnalTProb() - Method in class org.deeplearning4j.util.Viterbi
getLogPCorrect() - Method in class org.deeplearning4j.util.Viterbi
getLogPIncorrect() - Method in class org.deeplearning4j.util.Viterbi
getLogStates() - Method in class org.deeplearning4j.util.Viterbi
getLossFunction() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getLower(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
getLower() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
getLr() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: MNIST DB files start with unique integer number.
getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
getMask() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getMax() - Method in class org.deeplearning4j.util.SummaryStatistics
getMaxIterations() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
getMaxPointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getMean() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
getMean() - Method in class org.deeplearning4j.util.SummaryStatistics
getMetaStability() - Method in class org.deeplearning4j.util.Viterbi
getMin() - Method in class org.deeplearning4j.util.SummaryStatistics
getMomentum() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getMomentumAfter() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getMostPopulatedClusters(int) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getMostRecentClusterSetInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
getMostRecentIterationInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
getMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
getnIn() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getnLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Get the number of layers in the network
getNorthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getNorthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getnOut() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getNumberOfTrials() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
getNumChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
getNumColumns() - Method in class org.deeplearning4j.util.StringGrid
getNumDataSets() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
getNumIterations() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getNumLineSearchIterations() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getNumNames() - Method in class org.deeplearning4j.base.LFWLoader
getNumPixelColumns() - Method in class org.deeplearning4j.base.LFWLoader
getOptimizationAlgo() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getOptimizationPhaseCondition() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
getOptimizer() - Method in interface org.deeplearning4j.nn.api.Model: Returns this models optimizer
getOptimizer() - Method in class org.deeplearning4j.nn.layers.BaseLayer
getOptimizer() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
getOptimizer() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
getOptimizer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getOptimizer() - Method in class org.deeplearning4j.optimize.Solver
getOptimizer() - Method in class org.deeplearning4j.plot.BarnesHutTsne
getOutputLayer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Get the output layer
getPairIterator() - Method in class org.deeplearning4j.berkeley.CounterMap
getParam(String) - Method in interface org.deeplearning4j.nn.api.Model: Get the parameter
getParam(String) - Method in class org.deeplearning4j.nn.layers.BaseLayer
getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
getParam(String) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
getParam(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
getParams(NeuralNetConfiguration, Distribution) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
getParent() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
getParent() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getpCorrect() - Method in class org.deeplearning4j.util.Viterbi
getPoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
getPoint() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
getPoint() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
getPointDistanceFromCenterVariance() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getPointDistanceFromClusterVariance() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getPointDistribution() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
getPointLocationChange() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getPoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
getPoints() - Method in class org.deeplearning4j.clustering.Cluster
getPointsCount() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
getPointsFartherFromCenterThan(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getPossibleLabels() - Method in class org.deeplearning4j.util.Viterbi
getPredictedTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix: Computes the total number of times the class was predicted by the classifier.
getPreProcessor(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getPriority() - Method in class org.deeplearning4j.berkeley.PriorityQueue
getPriority() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Gets the priority of the highest-priority element of the queue.
getProbability(E) - Method in class org.deeplearning4j.berkeley.Counter: I know, I know, this should be wrapped in a Distribution class, but it's such a common use...why not.
getProbabilityOfSuccess() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
getProcessors() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
getResetAdaGradIterations() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getReverseSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getRight() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
getRight() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
getRng() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getRow(int) - Method in class org.deeplearning4j.clustering.cluster.Point
getRow(int) - Method in class org.deeplearning4j.util.StringGrid
getRows(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
getRows() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Number of rows per image.
getRowsWithColumnValues(Collection<String>, int) - Method in class org.deeplearning4j.util.StringGrid
getRowsWithDuplicateValuesInColumn(int) - Method in class org.deeplearning4j.util.StringGrid
getRowWithOnlyOneOccurrence(int) - Method in class org.deeplearning4j.util.StringGrid
getScalar(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
getScalar(int) - Method in class org.deeplearning4j.clustering.cluster.Point
getScalar(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
getSecond() - Method in class org.deeplearning4j.berkeley.Pair
getSecond() - Method in class org.deeplearning4j.berkeley.Triple
getSecondKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
getSeed() - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
getSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getSortedKeys() - Method in class org.deeplearning4j.berkeley.Counter
getSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getSouthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getSouthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
getSparsity() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getStates() - Method in class org.deeplearning4j.util.Viterbi
getStd() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
getStepFunction() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getStpmax() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
getStride() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getStringCollection(String) - Static method in class org.deeplearning4j.util.StringUtils: Returns a collection of strings.
getStrings(String) - Static method in class org.deeplearning4j.util.StringUtils: Returns an arraylist of strings.
getSum() - Method in class org.deeplearning4j.util.SummaryStatistics
getTerminationCondition() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
getTerminationCondition() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
getThird() - Method in class org.deeplearning4j.berkeley.Triple
getThreshold() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
getTokens() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
getTotalPointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
getTrimmedStringCollection(String) - Static method in class org.deeplearning4j.util.StringUtils: Splits a comma separated value String, trimming leading and trailing whitespace on each value.
getTrimmedStrings(String) - Static method in class org.deeplearning4j.util.StringUtils: Splits a comma separated value String, trimming leading and trailing whitespace on each value.
getType() - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
getType() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
getType() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
getType() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: The type of node; mainly extra meta data
getUniqueRows() - Method in class org.deeplearning4j.util.StringGrid
getUpper(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
getUpper() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
getValue() - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
getValue() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
getVariables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getVisibleUnit() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getWeightInit() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getWeightShape() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
getX() - Method in class org.deeplearning4j.clustering.quadtree.Cell
getY() - Method in class org.deeplearning4j.clustering.quadtree.Cell
getY() - Method in class org.deeplearning4j.plot.Tsne
getYGradient(int, INDArray, INDArray) - Method in class org.deeplearning4j.plot.Tsne
gibbhVh(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Gibbs sampling step: hidden ---> visible ---> hidden
goldLabel() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
gr(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Tests if a is greater than b.
gradient() - Method in interface org.deeplearning4j.nn.api.Model: Calculate a gradient
gradient(List<String>) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
gradient() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
Gradient - Interface in org.deeplearning4j.nn.gradient: Generic gradient
gradient(List<String>) - Method in interface org.deeplearning4j.nn.gradient.Gradient: The full gradient as one flat vector
gradient() - Method in interface org.deeplearning4j.nn.gradient.Gradient: The full gradient as one flat vector
gradient() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
gradient() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
gradient() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
gradient() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
gradient() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
gradient() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
gradient() - Method in class org.deeplearning4j.nn.layers.OutputLayer: Gets the gradient from one training iteration
gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
gradient() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
gradient(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
gradient() - Method in class org.deeplearning4j.plot.BarnesHutTsne
gradient(INDArray) - Method in class org.deeplearning4j.plot.Tsne
GRADIENT_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
GradientAdjustment - Class in org.deeplearning4j.optimize: Gradient adjustment
gradientAndScore() - Method in interface org.deeplearning4j.nn.api.Model: Get the gradient and score
gradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseLayer
gradientAndScore() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
gradientAndScore() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
gradientAndScore() - Method in class org.deeplearning4j.nn.layers.OutputLayer
gradientAndScore() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
gradientAndScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
gradientAndScore() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: The gradient and score for this optimizer
gradientAndScore() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
gradientAndScore() - Method in class org.deeplearning4j.plot.BarnesHutTsne
GradientAscent - Class in org.deeplearning4j.optimize.solvers: Vectorized Stochastic Gradient Ascent
GradientAscent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.GradientAscent
GradientAscent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.GradientAscent
gradientForVariable() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
gradientForVariable() - Method in interface org.deeplearning4j.nn.gradient.Gradient: Gradient look up table
GradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions: Normal gradient step function
GradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
GradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions: Normal gradient step function
GradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
GREATER - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
grow(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
gt(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
gt(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
gti(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
gti(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
gunzipFile(File, File) - Static method in class org.deeplearning4j.base.MnistFetcher

H

hashCode() - Method in class org.deeplearning4j.berkeley.Counter
hashCode() - Method in class org.deeplearning4j.berkeley.Pair
hashCode() - Method in class org.deeplearning4j.berkeley.Triple
hashCode() - Method in class org.deeplearning4j.clustering.quadtree.Cell
hashCode() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
hashCode() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
hashCode() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
hashCode() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
hashCode() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
hashCode() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.LSTM
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.RBM
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder
hashCode() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
hashCode() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
hashCode() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
hashCode() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
hashCode() - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
hashCode() - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
hashCode() - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
hashCode() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
hashCode() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
hashCode() - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
hashCode() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
hashCode() - Method in class org.deeplearning4j.util.Index
hashCode() - Method in class org.deeplearning4j.util.MultiDimensionalMap
HashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.HashMapFactory
hashSet() - Static method in class org.deeplearning4j.util.MultiDimensionalSet
hasMore() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
hasMore() - Method in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
hasMore() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Whether the dataset has more to load
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
hasNext() - Method in class org.deeplearning4j.berkeley.PriorityQueue
hasNext() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Returns true if the priority queue is non-empty
hasNext() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
hasNext() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
hasNext() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
hasNext() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Returns true if the iteration has more elements.
hasNext() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Returns true if the iteration has more elements.
hasNext() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
hasNext() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
hBeta(INDArray, double) - Method in class org.deeplearning4j.plot.Tsne: Computes a gaussian kernel given a vector of squared distance distances
head(int) - Method in class org.deeplearning4j.util.StringGrid
heapifyDown(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
heapifyUp(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
HeapItem - Class in org.deeplearning4j.clustering.sptree
HeapItem(int, double) - Constructor for class org.deeplearning4j.clustering.sptree.HeapItem
hexStringToByte(String) - Static method in class org.deeplearning4j.util.StringUtils: Given a hexstring this will return the byte array corresponding to the string
hiddenLayerSizes - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
hiddenLayerSizes(int...) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder: Specify the hidden layer sizes.
hiddenLayerSizes - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
hiddenLayerSizes(int...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
hiddenSigma - Variable in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
hiddenUnit(RBM.HiddenUnit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
hist(Layer, Gradient) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
hist(Layer) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
histogram(String[], INDArray[]) - Method in class org.deeplearning4j.plot.NeuralNetPlotter: Histograms the given matrices.
humanReadableInt(long) - Static method in class org.deeplearning4j.util.StringUtils: Given an integer, return a string that is in an approximate, but human readable format.
hypergeometric(int, int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Find a hypergeometric distribution.
HyperRect - Class in org.deeplearning4j.clustering.kdtree: Created by agibsonccc on 12/29/14.
HyperRect(List<HyperRect.Interval>) - Constructor for class org.deeplearning4j.clustering.kdtree.HyperRect
HyperRect.Interval - Class in org.deeplearning4j.clustering.kdtree
hypotenuse(double, double) - Static method in class org.deeplearning4j.util.MathUtils: sqrt(a^2 + b^2) without under/overflow.

I

id() - Method in class org.deeplearning4j.clustering.cluster.Point
IdentityHashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
idf(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Inverse document frequency: the total docs divided by the number of times the word appeared in a document
ImageLoader - Class in org.deeplearning4j.util: Image loader for taking images and converting them to matrices
ImageLoader() - Constructor for class org.deeplearning4j.util.ImageLoader
ImageLoader(int, int) - Constructor for class org.deeplearning4j.util.ImageLoader
ImageVectorizer - Class in org.deeplearning4j.datasets.vectorizer: An image vectorizer takes an input image (RGB) and transforms it in to a data applyTransformToDestination
ImageVectorizer(File, int, int) - Constructor for class org.deeplearning4j.datasets.vectorizer.ImageVectorizer: Baseline knowledge needed for the vectorizer
incrementAll(Collection<? extends E>, double) - Method in class org.deeplearning4j.berkeley.Counter: Increment each element in a given collection by a given amount.
incrementAll(Counter<T>) - Method in class org.deeplearning4j.berkeley.Counter
incrementAll(Map<K, V>, double) - Method in class org.deeplearning4j.berkeley.CounterMap
incrementAll(CounterMap<K, V>) - Method in class org.deeplearning4j.berkeley.CounterMap
incrementCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter: Increment a key's count by the given amount.
incrementCount(K, V, double) - Method in class org.deeplearning4j.berkeley.CounterMap: Increments the count for a particular (key, value) pair.
incrementFalseNegatives(int) - Method in class org.deeplearning4j.eval.Evaluation
incrementFalsePositives(int) - Method in class org.deeplearning4j.eval.Evaluation
incrementTruePositives(int) - Method in class org.deeplearning4j.eval.Evaluation
index(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
Index - Class in org.deeplearning4j.util: An index is a transform of objects augmented with a list and a reverse lookup table for fast lookups.
Index() - Constructor for class org.deeplearning4j.util.Index
indexOf(Object) - Method in class org.deeplearning4j.util.Index
information(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the entropy for a given vector of probabilities.
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.ParamInitializer: Initialize the parameters
init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in interface org.deeplearning4j.nn.api.ParamInitializer: Initialization via extra parameters where necessary
init() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Initialize
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.RecursiveParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.SubsampleParamInitializer
init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.SubsampleParamInitializer
initCalled - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
initClusters() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
initialClusterCount - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
initialize(ClusterSet, boolean) - Static method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
initialize(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels from this dataset
initializeCurrFromList(List<DataSet>) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher: Initializes this data applyTransformToDestination fetcher from the passed in datasets
initializeLayers(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Base class for initializing the neuralNets based on the input.
initializer() - Method in interface org.deeplearning4j.nn.api.LayerFactory: Get the param initializer used for initializing layers
initializer() - Method in class org.deeplearning4j.nn.layers.factory.ConvolutionLayerFactory
initializer() - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
initializer() - Method in class org.deeplearning4j.nn.layers.factory.LSTMLayerFactory
initializer() - Method in class org.deeplearning4j.nn.layers.factory.PretrainLayerFactory
initializer() - Method in class org.deeplearning4j.nn.layers.factory.RecursiveAutoEncoderLayerFactory
initializer() - Method in class org.deeplearning4j.nn.layers.factory.SubsampleLayerFactory
initialMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
initialMomentum - Variable in class org.deeplearning4j.plot.Tsne
initParams() - Method in interface org.deeplearning4j.nn.api.Model: Initialize the parameters
initParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
initParams() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
initParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
initParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
initParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
initWeights(int[], float, float) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
initWeights(int[], WeightInit, Distribution) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Initializes a matrix with the given weight initialization scheme
initWeights(int, int, WeightInit, Distribution) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Initializes a matrix with the given weight initialization scheme
input() - Method in interface org.deeplearning4j.nn.api.Model: The input/feature matrix for the model
input - Variable in class org.deeplearning4j.nn.layers.BaseLayer
input() - Method in class org.deeplearning4j.nn.layers.BaseLayer
input() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
input() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
input - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
input() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
input() - Method in class org.deeplearning4j.plot.BarnesHutTsne
inputColumns() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
inputColumns - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
inputColumns() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
inputColumns() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
inputColumns() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: The length of a feature vector for an individual example
inputColumns() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
inputColumns() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Input columns for the dataset
inputColumns() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Input columns for the dataset
inputColumns() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
inputColumns() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
InputPreProcessor - Interface in org.deeplearning4j.nn.conf: Input pre processor used for pre processing input before passing it to the neural network.
inputPreProcessor - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
inputPreProcessor(Integer, InputPreProcessor) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
inputPreProcessors(Map<Integer, InputPreProcessor>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder: Specify the input pre processors.
inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
InputSplit - Class in org.deeplearning4j.util
InputSplit() - Constructor for class org.deeplearning4j.util.InputSplit
inputStreamFromPath(String) - Static method in class org.deeplearning4j.util.DeepLearningIOUtil
insert(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree: Insert a point in to the tree
insert(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Insert an index of the data in to the tree
intersection(Collection<T>, Collection<T>) - Static method in class org.deeplearning4j.util.SetUtils
intersectionP(Set<? extends T>, Set<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils
Interval(double, double) - Constructor for class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
intializeConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
intPow(int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: exponentiation like we learned in grade school: multiply b by itself e times.
intPow(float, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: exponentiation like we learned in grade school: multiply b by itself e times.
intPow(double, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: exponentiation like we learned in grade school: multiply b by itself e times.
InvalidStepException - Exception in org.deeplearning4j.exception: Created by agibsonccc on 8/20/14.
InvalidStepException(String) - Constructor for exception org.deeplearning4j.exception.InvalidStepException: Constructs a new exception with the specified detail message.
InvalidStepException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException: Constructs a new exception with the specified detail message and cause.
InvalidStepException(Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) (which typically contains the class and detail message of cause).
InvalidStepException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.InvalidStepException: Constructs a new exception with the specified detail message, cause, suppression enabled or disabled, and writable stack trace enabled or disabled.
inverse(RBM.HiddenUnit) - Static method in class org.deeplearning4j.util.RBMUtil
inverse(RBM.VisibleUnit) - Static method in class org.deeplearning4j.util.RBMUtil
invert() - Method in class org.deeplearning4j.berkeley.CounterMap: Constructs reverse CounterMap where the count of a pair (k,v) is the count of (v,k) in the current CounterMap
iris() - Static method in class org.deeplearning4j.datasets.DataSets
iris(int) - Static method in class org.deeplearning4j.datasets.DataSets
IrisDataFetcher - Class in org.deeplearning4j.datasets.fetchers
IrisDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
IrisDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
IrisDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator
IrisUtils - Class in org.deeplearning4j.base
IrisUtils() - Constructor for class org.deeplearning4j.base.IrisUtils
isAllowEmptyClusters() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
isAllowEmptyClusters() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
isApplySparsity() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
isBackward() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
isCleanedUp() - Method in class org.deeplearning4j.clustering.cluster.Point
isClusteringOptimizationType(ClusteringOptimizationType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
isColumnVector() - Method in class org.deeplearning4j.clustering.cluster.Point
isConstrainGradientToUnitNorm() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
isConverged() - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
isCorrect() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Returns whether the tree is consistent or not
isCorrect() - Method in class org.deeplearning4j.clustering.sptree.SpTree: Verifies the structure of the tree (does bounds checking on each node)
isDangerous(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns true if the argument is a "dangerous" double to have around, namely one that is infinite, NaN or zero.
isDangerous(float) - Static method in class org.deeplearning4j.berkeley.SloppyMath
isDiscreteProb(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
isEmpty() - Method in class org.deeplearning4j.berkeley.Counter: True if there are no entries in the counter (false does not mean totalCount > 0)
isEmpty() - Method in class org.deeplearning4j.berkeley.CounterMap: True if there are no entries in the CounterMap (false does not mean totalCount > 0)
isEmpty() - Method in class org.deeplearning4j.berkeley.PriorityQueue
isEmpty() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: True if the queue is empty (size == 0).
isEmpty() - Method in class org.deeplearning4j.clustering.cluster.Cluster
isEmpty() - Method in class org.deeplearning4j.util.DiskBasedQueue
isEmpty() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns true if this map contains no key-value mappings.
isEmpty() - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns true if this applyTransformToDestination contains no elements.
isEqualTo(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
isEqualTo(CounterMap<K, V>) - Method in class org.deeplearning4j.berkeley.CounterMap
isGreater(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
isLeaf() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
isLeaf() - Method in class org.deeplearning4j.clustering.sptree.SpTree
isLeaf() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns whether the node has any children or not
isMatrix() - Method in class org.deeplearning4j.clustering.cluster.Point
isMinimize() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
isNewLocation() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
isOptimizationApplicableNow(IterationHistory) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
isOptimizationDefined() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
isOptimizationDefined() - Method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
isOptimizationDefined() - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
isPreTerminal() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Node has one child that is a leaf
isPretrain() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
isRowVector() - Method in class org.deeplearning4j.clustering.cluster.Point
isSatisfied(IterationHistory) - Method in interface org.deeplearning4j.clustering.algorithm.condition.ClusteringAlgorithmCondition
isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.ConvergenceCondition
isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
isScalar() - Method in class org.deeplearning4j.clustering.cluster.Point
isSquare() - Method in class org.deeplearning4j.clustering.cluster.Point
isStrategyApplied() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
isStrategyOfType(ClusteringStrategyType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
isStrategyOfType(ClusteringStrategyType) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
isUseAdaGrad() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
isUseDropConnect() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
isUseGaussNewtonVectorProductBackProp() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
isUseRBMPropUpAsActivations() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
isUseRegularization() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
isVector() - Method in class org.deeplearning4j.clustering.cluster.Point
isVeryDangerous(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns true if the argument is a "very dangerous" double to have around, namely one that is infinite or NaN.
iterate(INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Run one iteration
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer: iterate one iteration of the network
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
iterate(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
iterate(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
iteration - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
iterationCountGreaterThan(int) - Static method in class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
iterationDone(Model, int) - Method in interface org.deeplearning4j.optimize.api.IterationListener: Event listener for each iteration
iterationDone(Model, int) - Method in class org.deeplearning4j.optimize.listeners.ComposableIterationListener
iterationDone(Model, int) - Method in class org.deeplearning4j.optimize.listeners.ScoreIterationListener
iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
IterationGradientDescent - Class in org.deeplearning4j.optimize.solvers: No line search gradient descent
IterationGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.IterationGradientDescent
IterationGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.IterationGradientDescent
IterationHistory - Class in org.deeplearning4j.clustering.algorithm.iteration
IterationHistory() - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
IterationInfo - Class in org.deeplearning4j.clustering.algorithm.iteration
IterationInfo(int) - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
IterationInfo(int, ClusterSetInfo) - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
IterationListener - Interface in org.deeplearning4j.optimize.api: Each epoch the listener is called, mainly used for debugging or visualizations
iterationListener - Variable in class org.deeplearning4j.plot.Tsne
iterationListeners - Variable in class org.deeplearning4j.nn.layers.BaseLayer
iterationListeners - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
iterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
iterator() - Method in class org.deeplearning4j.util.DiskBasedQueue
iterator() - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns an iterator over the elements in this applyTransformToDestination.
IteratorIterator(Iterator, Factory<Iterator<T>>) - Constructor for class org.deeplearning4j.berkeley.Iterators.IteratorIterator
Iterators - Class in org.deeplearning4j.berkeley
Iterators.FilteredIterator<T> - Class in org.deeplearning4j.berkeley: Creates an iterator that only returns items of a base iterator that pass a filter.
Iterators.IteratorIterator<T> - Class in org.deeplearning4j.berkeley: Wraps a two-level iteration scenario in an iterator.
Iterators.Transform<S,T> - Class in org.deeplearning4j.berkeley: WraTps a base iterator with a transformation function.
Iterators.TransformingIterator<I,O> - Class in org.deeplearning4j.berkeley

J

join(Iterable, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Joins each elem in the Collection with the given glue.
join(List<?>, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Joins each elem in the List with the given glue.
join(Object[], String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Joins each elem in the array with the given glue.
join(List) - Static method in class org.deeplearning4j.berkeley.StringUtils: Joins elems with a space.
join(Object[]) - Static method in class org.deeplearning4j.berkeley.StringUtils: Joins elems with a space.
join(CharSequence, Iterable<String>) - Static method in class org.deeplearning4j.util.StringUtils: Concatenates strings, using a separator.
joinObjects(CharSequence, Iterable<? extends Object>) - Static method in class org.deeplearning4j.util.StringUtils: Concatenates stringified objects, using a separator.

K

k(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
k - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
KDNode(INDArray) - Constructor for class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
KDTree - Class in org.deeplearning4j.clustering.kdtree: KDTree based on: https://github.com/nicky-zs/kdtree-python/blob/master/kdtree.py
KDTree(int) - Constructor for class org.deeplearning4j.clustering.kdtree.KDTree
KDTree.KDNode - Class in org.deeplearning4j.clustering.kdtree
keepBottomNKeys(int) - Method in class org.deeplearning4j.berkeley.Counter
keepTopNKeys(int) - Method in class org.deeplearning4j.berkeley.Counter
kernel(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
kernel - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
key(String, Object...) - Method in class org.deeplearning4j.util.FingerPrintKeyer
keySet() - Method in class org.deeplearning4j.berkeley.Counter: The elements in the counter.
keySet() - Method in class org.deeplearning4j.berkeley.CounterMap: Returns the keys that have been inserted into this CounterMap.
keySet() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns a Set view of the keys contained in this map.
KMeansClustering - Class in org.deeplearning4j.clustering.kmeans
KMeansClustering(ClusteringStrategy) - Constructor for class org.deeplearning4j.clustering.kmeans.KMeansClustering
knn(INDArray, double) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
kroneckerDelta(double, double) - Static method in class org.deeplearning4j.util.MathUtils: This returns the kronecker delta of two doubles.

L

l1(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
l2(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
l2 - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
label() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
labelProbabilities(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Returns the probabilities for each label for each example row wise
labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Returns the probabilities for each label for each example row wise
labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Returns the probabilities for each label for each example row wise
labels - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
lambert(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
lastChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
Layer - Interface in org.deeplearning4j.nn.api: Interface for a layer of a neural network.
Layer - Class in org.deeplearning4j.nn.conf.layers: A neural network layer.
Layer() - Constructor for class org.deeplearning4j.nn.conf.layers.Layer
layer(Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
layer - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
Layer.Type - Enum in org.deeplearning4j.nn.api
layerConfig - Variable in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
LayerFactories - Class in org.deeplearning4j.nn.layers.factory: Static method for finding which layer factory to use
LayerFactories() - Constructor for class org.deeplearning4j.nn.layers.factory.LayerFactories
LayerFactory - Interface in org.deeplearning4j.nn.api: Common interface for creating neural network layers.
LayerOverride - Class in org.deeplearning4j.nn.conf.override: Layer override
LayerOverride(int, Layer) - Constructor for class org.deeplearning4j.nn.conf.override.LayerOverride
layers - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
layerWiseConfigurations - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
LBFGS - Class in org.deeplearning4j.optimize.solvers: LBFGS
LBFGS(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
LBFGS(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
learningRate(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
learningRate(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
learningRate - Variable in class org.deeplearning4j.plot.Tsne.Builder
learningRate(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
learningRate - Variable in class org.deeplearning4j.plot.Tsne
leftChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
length() - Method in class org.deeplearning4j.clustering.cluster.Point
LESS - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
LexicographicPairComparator(Comparator<F>, Comparator<S>) - Constructor for class org.deeplearning4j.berkeley.Pair.LexicographicPairComparator
LFW - Static variable in class org.deeplearning4j.base.LFWLoader
lfw() - Static method in class org.deeplearning4j.datasets.DataSets
lfw(int) - Static method in class org.deeplearning4j.datasets.DataSets
LFW_URL - Static variable in class org.deeplearning4j.base.LFWLoader
LFWDataFetcher - Class in org.deeplearning4j.datasets.fetchers: Data fetcher for the LFW faces dataset
LFWDataFetcher(int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
LFWDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
LFWDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
LFWDataSetIterator(int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
LFWDataSetIterator(int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
LFWDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
LFWDataSetIterator(int, int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
LFWLoader - Class in org.deeplearning4j.base: Loads LFW faces data transform.
LFWLoader() - Constructor for class org.deeplearning4j.base.LFWLoader
LFWLoader(int, int) - Constructor for class org.deeplearning4j.base.LFWLoader
limitDecimalTo2(double) - Static method in class org.deeplearning4j.util.StringUtils
linearIndex(int) - Method in class org.deeplearning4j.clustering.cluster.Point
linearView() - Method in class org.deeplearning4j.clustering.cluster.Point
linearViewColumnOrder() - Method in class org.deeplearning4j.clustering.cluster.Point
lineMaximizer - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
LineOptimizer - Interface in org.deeplearning4j.optimize.api: Line optimizer interface adapted from mallet
lineSearch(double, INDArray, INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree: Search with the proposed objective
list(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
ListBuilder(List<NeuralNetConfiguration.Builder>) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
ListDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl: Wraps a data applyTransformToDestination collection
ListDataSetIterator(Collection<DataSet>, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
ListDataSetIterator(Collection<DataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator: Initializes with a batch of 5
listener(IterationListener...) - Method in class org.deeplearning4j.optimize.Solver.Builder
listeners(Collection<IterationListener>) - Method in class org.deeplearning4j.optimize.Solver.Builder
LoadAndDraw - Class in org.deeplearning4j.datasets.mnist.draw
LoadAndDraw() - Constructor for class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
loadIris(int, int) - Static method in class org.deeplearning4j.base.IrisUtils
LOCAL_DIR_NAME - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
log - Static variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
log - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
log - Static variable in class org.deeplearning4j.plot.Tsne
log2 - Static variable in class org.deeplearning4j.util.MathUtils: The natural logarithm of 2.
log2(double) - Static method in class org.deeplearning4j.util.MathUtils: Returns the logarithm of a for base 2.
logAdd(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the log of the sum of two numbers, which are themselves input in log form.
logAdd(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the log of the sum of two numbers, which are themselves input in log form.
logAdd(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd(double[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd(List<Double>) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd(float[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd(double[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd(Counter<T>) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logAdd_Old(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logNormalize(double[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
logs2probs(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.
logSubtract(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
LOGTOLERANCE - Static variable in class org.deeplearning4j.berkeley.SloppyMath: If a difference is bigger than this in log terms, then the sum or difference of them will just be the larger (to 12 or so decimal places for double, and 7 or 8 for float).
longestCommonSubstring(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Computes the longest common substring of s and t.
lookingAt(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Say whether this regular expression can be found at the beginning of this String.
lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
lossFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
LSTM - Class in org.deeplearning4j.nn.conf.layers: LSTM recurrent net.
LSTM() - Constructor for class org.deeplearning4j.nn.conf.layers.LSTM
LSTM - Class in org.deeplearning4j.nn.layers.recurrent: LSTM recurrent net.
LSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LSTM
LSTMLayerFactory - Class in org.deeplearning4j.nn.layers.factory: LSTM layer initializer
LSTMLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.LSTMLayerFactory
LSTMParamInitializer - Class in org.deeplearning4j.nn.params: LSTM Parameters.
LSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.LSTMParamInitializer
lt(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
lt(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
lti(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
lti(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point

M

main(String[]) - Static method in class org.deeplearning4j.berkeley.Counter
main(String[]) - Static method in class org.deeplearning4j.berkeley.CounterMap
main(String[]) - Static method in class org.deeplearning4j.berkeley.PriorityQueue
main(String[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Tests the hypergeometric distribution code, or other cooccurrences provided in this module.
main(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
main(String[]) - Static method in class org.deeplearning4j.datasets.creator.MnistDataSetCreator
main(String[]) - Static method in class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
main(String[]) - Static method in class org.deeplearning4j.eval.ConfusionMatrix
majorStride() - Method in class org.deeplearning4j.clustering.cluster.Point
makePair(S, T) - Static method in class org.deeplearning4j.berkeley.Pair
makeTriple(S, T, U) - Static method in class org.deeplearning4j.berkeley.Triple
manhattanDistance(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This will calculate the Manhattan distance between two sets of points.
mapByPrimaryKey(int) - Method in class org.deeplearning4j.util.StringGrid
MapFactory<K,V> - Class in org.deeplearning4j.berkeley: The MapFactory is a mechanism for specifying what kind of map is to be used by some object.
MapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory
MapFactory.HashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
MapFactory.IdentityHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
MapFactory.TreeMapFactory<K,V> - Class in org.deeplearning4j.berkeley
MapFactory.WeakHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
mapper() - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Object mapper for serialization of configurations
mask - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
MASTER_PATH - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
MASTER_URL - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
matches(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Say whether this regular expression matches this String.
MathUtils - Class in org.deeplearning4j.util: This is a math utils class.
MathUtils() - Constructor for class org.deeplearning4j.util.MathUtils
max() - Method in class org.deeplearning4j.berkeley.Counter
max(int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the minimum of three int values.
max(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the greater of two float values.
max(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the greater of two double values.
max(int) - Method in class org.deeplearning4j.clustering.cluster.Point
max(double[]) - Static method in class org.deeplearning4j.util.MathUtils
maxIndex(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Returns index of maximum element in a given array of doubles.
maxIter - Variable in class org.deeplearning4j.plot.Tsne.Builder
maxIter - Variable in class org.deeplearning4j.plot.Tsne
maxLengthIterator(Iterator<T>, int) - Static method in class org.deeplearning4j.berkeley.Iterators: Provides a max number of elements for an underlying base iterator.
mean(int) - Method in class org.deeplearning4j.clustering.cluster.Point
mean(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Computes the mean for an array of doubles.
merge(Layer, int) - Method in interface org.deeplearning4j.nn.api.Layer: Parameter averaging
merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.BaseLayer: Averages the given logistic regression from a mini batch in to this one
merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
merge(MultiLayerNetwork, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Merges this network with the other one.
merge(int, int) - Method in class org.deeplearning4j.util.StringGrid
mergeCoords(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This will merge the coordinates of the given coordinate system.
mergeCoords(List<Double>, List<Double>) - Static method in class org.deeplearning4j.util.MathUtils: This will merge the coordinates of the given coordinate system.
min() - Method in class org.deeplearning4j.berkeley.Counter
min(int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the minimum of three int values.
min(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the smaller of two float values.
min(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Returns the smaller of two double values.
min(int) - Method in class org.deeplearning4j.clustering.cluster.Point
min(double[]) - Static method in class org.deeplearning4j.util.MathUtils
minDistance(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
minGain(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
minGain - Variable in class org.deeplearning4j.plot.Tsne.Builder
minGain(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
minGain - Variable in class org.deeplearning4j.plot.Tsne
minimize(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
minimize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
mmul(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mmul(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mmuli(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mmuli(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mnist() - Static method in class org.deeplearning4j.datasets.DataSets
mnist(int) - Static method in class org.deeplearning4j.datasets.DataSets
MnistDataFetcher - Class in org.deeplearning4j.datasets.fetchers: Data fetcher for the MNIST dataset
MnistDataFetcher(boolean) - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher: Constructor telling whether to binarize the dataset or not
MnistDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
MnistDataSetCreator - Class in org.deeplearning4j.datasets.creator
MnistDataSetCreator() - Constructor for class org.deeplearning4j.datasets.creator.MnistDataSetCreator
MnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl: Mnist data applyTransformToDestination iterator.
MnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
MnistDataSetIterator(int, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator: Whether to binarize the data or not
MnistDbFile - Class in org.deeplearning4j.datasets.mnist: MNIST database file containing entries that can represent image or label data.
MnistDbFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistDbFile: Creates new instance and reads the header information.
MnistFetcher - Class in org.deeplearning4j.base
MnistFetcher() - Constructor for class org.deeplearning4j.base.MnistFetcher
MnistImageFile - Class in org.deeplearning4j.datasets.mnist: MNIST database image file.
MnistImageFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistImageFile: Creates new MNIST database image file ready for reading.
MnistLabelFile - Class in org.deeplearning4j.datasets.mnist: MNIST database label file.
MnistLabelFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistLabelFile: Creates new MNIST database label file ready for reading.
MnistManager - Class in org.deeplearning4j.datasets.mnist: Utility class for working with the MNIST database.
MnistManager(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistManager: Constructs an instance managing the two given data files.
Model - Interface in org.deeplearning4j.nn.api: A Model is meant for predicting something from data.
model(Model) - Method in class org.deeplearning4j.optimize.Solver.Builder
model - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
momentum(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
momentum - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
momentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
momentum - Variable in class org.deeplearning4j.plot.Tsne
momentumAfter(Map<Integer, Double>) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
momentumAfter - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
mostLikelyInSequence(INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
movingAverage(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils: Calculate a moving average given the length
MovingWindowBaseDataSetIterator - Class in org.deeplearning4j.datasets.iterator: DataSetIterator for moving window (rotating matrices)
MovingWindowBaseDataSetIterator(int, int, DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.MovingWindowBaseDataSetIterator
MovingWindowDataSetFetcher - Class in org.deeplearning4j.datasets.iterator.impl: Moving window data fetcher.
MovingWindowDataSetFetcher(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher
MovingWindowMatrix - Class in org.deeplearning4j.util: Moving window on a matrix (usually used for images) Given a: This is a list of flattened arrays: 1 1 1 1 1 1 2 2 2 2 2 2 ----> 1 1 2 2 3 3 3 3 3 3 4 4 4 4 4 4 3 3 4 4
MovingWindowMatrix(INDArray, int, int, boolean) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix
MovingWindowMatrix(INDArray, int, int) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix: Same as calling new MovingWindowMatrix(toSlice,windowRowSize,windowColumnSize,false)
mul(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
mul(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mul(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mul(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mul(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
mul(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mulColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
muli(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muliColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
muliRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
mulRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
MULTI_LAYER_CONF - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
MultiDimensionalMap<K,T,V> - Class in org.deeplearning4j.util: Multiple key map
MultiDimensionalMap(Map<Pair<K, T>, V>) - Constructor for class org.deeplearning4j.util.MultiDimensionalMap
MultiDimensionalMap.Entry<K,T,V> - Class in org.deeplearning4j.util
MultiDimensionalSet<K,V> - Class in org.deeplearning4j.util: Created by agibsonccc on 4/29/14.
MultiDimensionalSet(Set<Pair<K, V>>) - Constructor for class org.deeplearning4j.util.MultiDimensionalSet
MultiLayerConfiguration - Class in org.deeplearning4j.nn.conf: Configuration for a multi layer network
MultiLayerConfiguration() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration
MultiLayerConfiguration(MultiLayerConfiguration) - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration
MultiLayerConfiguration.Builder - Class in org.deeplearning4j.nn.conf
MultiLayerNetwork - Class in org.deeplearning4j.nn.multilayer: A base class for a multi layer neural network with a logistic output layer and multiple hidden neuralNets.
MultiLayerNetwork(MultiLayerConfiguration) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
MultiLayerNetwork(String, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Initialize the network based on the configuration
MultiLayerNetwork(MultiLayerConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Initialize the network based on the configuraiton
MultiLayerNetworkReconstructionRender - Class in org.deeplearning4j.plot: Reconstruction renders for a multi layer network
MultiLayerNetworkReconstructionRender(DataSetIterator, MultiLayerNetwork, int) - Constructor for class org.deeplearning4j.plot.MultiLayerNetworkReconstructionRender
MultiLayerNetworkReconstructionRender(DataSetIterator, MultiLayerNetwork) - Constructor for class org.deeplearning4j.plot.MultiLayerNetworkReconstructionRender
MultiLayerUtil - Class in org.deeplearning4j.util: Various cooccurrences for manipulating a multi layer network
MultiLayerUtil() - Constructor for class org.deeplearning4j.util.MultiLayerUtil
MultipleEpochsIterator - Class in org.deeplearning4j.datasets.iterator: A dataset iterator for doing multiple passes over a dataset
MultipleEpochsIterator(int, DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
MultiThreadUtils - Class in org.deeplearning4j.util
MultiThreadUtils() - Constructor for class org.deeplearning4j.util.MultiThreadUtils
MyMethod<I,O> - Interface in org.deeplearning4j.berkeley: A function wrapping interface.

N

NAME_SPACE - Static variable in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory
nChooseK(int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Computes n choose k in an efficient way.
nearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
nearestCluster(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
neg() - Method in class org.deeplearning4j.clustering.cluster.Point
negative() - Method in class org.deeplearning4j.eval.Evaluation: Total negatives true negatives + falseNegatives
NegativeDefaultStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions: Inverse step function
NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
NegativeDefaultStepFunction - Class in org.deeplearning4j.optimize.stepfunctions: Inverse step function
NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
NegativeGradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions: Subtract the line
NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
NegativeGradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions: Subtract the line
NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
negi() - Method in class org.deeplearning4j.clustering.cluster.Point
neq(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
neq(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
neqi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
neqi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
NEURAL_NET_CONF - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
NeuralNetConfiguration - Class in org.deeplearning4j.nn.conf: A Serializable configuration for neural nets that covers per layer parameters
NeuralNetConfiguration() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
NeuralNetConfiguration(double, boolean, double, double, int, double, double, boolean, Map<Integer, Double>, int, int, double, boolean, WeightInit, OptimizationAlgorithm, LossFunctions.LossFunction, boolean, Random, Distribution, StepFunction, Layer, List<String>, int, int, String, RBM.VisibleUnit, RBM.HiddenUnit, int, int[], int[], int[], int, int, boolean, ConvolutionDownSampleLayer.ConvolutionType) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
NeuralNetConfiguration(double, boolean, double, int, double, int, double, double, boolean, Map<Integer, Double>, int, double, boolean, WeightInit, OptimizationAlgorithm, LossFunctions.LossFunction, boolean, Random, Distribution, int, int, String, RBM.VisibleUnit, RBM.HiddenUnit, int[], int[], int[], int[], int, int, int, boolean, Layer, ConvolutionDownSampleLayer.ConvolutionType, double) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
NeuralNetConfiguration(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
NeuralNetConfiguration.Builder - Class in org.deeplearning4j.nn.conf
NeuralNetConfiguration.ListBuilder - Class in org.deeplearning4j.nn.conf: Fluent interface for building a list of configurations
NeuralNetPlotter - Class in org.deeplearning4j.plot: Credit to : http://yosinski.com/media/papers/Yosinski2012VisuallyDebuggingRestrictedBoltzmannMachine.pdf for visualizations
NeuralNetPlotter() - Constructor for class org.deeplearning4j.plot.NeuralNetPlotter
NeuralNetPlotterIterationListener - Class in org.deeplearning4j.plot.iterationlistener: Renders network activations every n iterations
NeuralNetPlotterIterationListener(int, NeuralNetPlotter, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
NeuralNetPlotterIterationListener(int, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
NeuralNetPlotterIterationListener(int, NeuralNetPlotter, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
NeuralNetPlotterIterationListener(int, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
NeuralNetPlotterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
NeuralNetworkReconstructionRender - Class in org.deeplearning4j.plot: Neural Network reconstruction renderer
NeuralNetworkReconstructionRender(DataSetIterator, Layer) - Constructor for class org.deeplearning4j.plot.NeuralNetworkReconstructionRender
newExecutorService() - Static method in class org.deeplearning4j.util.MultiThreadUtils
newHashBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap: Thread safe hash map impl
newInstance(Object...) - Method in class org.deeplearning4j.berkeley.Factory.DefaultFactory
newInstance(Object...) - Method in interface org.deeplearning4j.berkeley.Factory
newInstance(Class<T>, Configuration) - Static method in class org.deeplearning4j.util.ReflectionUtils: Create an object for the given class and initialize it from conf
newIterable(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators: Wraps an iterator as an iterable
newPair(S, T) - Static method in class org.deeplearning4j.berkeley.Pair
newThreadSafeHashBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap: Thread safe hash map implementation
newThreadSafeTreeBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap: Thread safe sorted map implementation
newTreeBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap: Tree map implementation
next() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
next() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
next() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
next() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
next() - Method in class org.deeplearning4j.berkeley.PriorityQueue
next() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Returns the element in the queue with highest priority, and pops it from the queue.
next(int) - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
next() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
next() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
next() - Method in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
next() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
next() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
next(int) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
next() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Returns the next data applyTransformToDestination
next() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
next(int) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Like the standard next method but allows a customizable number of examples returned
next() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Returns the next element in the iteration.
next(int) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Like the standard next method but allows a customizable number of examples returned
next() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Returns the next element in the iteration.
next() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
next(int) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
next() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: Move to the next entry.
next() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
next(int) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
nextImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Move the cursor to the next image.
nextList(List<Iterator<T>>) - Static method in class org.deeplearning4j.berkeley.Iterators
nextPowOf2(long) - Static method in class org.deeplearning4j.util.MathUtils: See: http://stackoverflow.com/questions/466204/rounding-off-to-nearest-power-of-2
nIn(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
nIn - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
nn(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree: Query for nearest neighbor.
Node(int, double) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree.Node
NODE_RATIO - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
noNaNDivide(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
NONE - Static variable in class org.deeplearning4j.util.StringGrid
norm1(int) - Method in class org.deeplearning4j.clustering.cluster.Point
norm2(int) - Method in class org.deeplearning4j.clustering.cluster.Point
Norm2Termination - Class in org.deeplearning4j.optimize.terminations: Terminate if the norm2 of the gradient is < a certain tolerance
Norm2Termination(double) - Constructor for class org.deeplearning4j.optimize.terminations.Norm2Termination
NormalDistribution - Class in org.deeplearning4j.nn.conf.distribution: A normal distribution.
NormalDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.NormalDistribution: Create a normal distribution with the given mean and std
normalize() - Method in class org.deeplearning4j.berkeley.Counter: Destructively normalize this Counter in place.
normalize() - Method in class org.deeplearning4j.berkeley.CounterMap
normalize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer: Normalize the input image by row sums
normalize(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
normalize - Variable in class org.deeplearning4j.plot.Tsne.Builder
normalize(boolean) - Method in class org.deeplearning4j.plot.Tsne.Builder
normalize - Variable in class org.deeplearning4j.plot.Tsne
normalize(double, double, double) - Static method in class org.deeplearning4j.util.MathUtils: Normalize a value (val - min) / (max - min)
normalize(double[], double) - Static method in class org.deeplearning4j.util.MathUtils: Normalizes the doubles in the array using the given value.
normalized(int[], int) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Normalized weight init
normalizeToOne(double[]) - Static method in class org.deeplearning4j.util.MathUtils
normalizeWithDiscount(double) - Method in class org.deeplearning4j.berkeley.CounterMap
normmax(int) - Method in class org.deeplearning4j.clustering.cluster.Point
nOut(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
nOut - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
nthIndex(String, char, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns the index of the nth occurrence of ch in s, or -1 if there are less than n occurrences of ch.
NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
NUM_IMAGES - Static variable in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
NUM_PASSES - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
numExamples() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
numExamples - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
numExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
numExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
numExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Total number of examples in the dataset
numExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Total number of examples in the dataset
numExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
numExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
numFeatureMap(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils: Retrieve the number of feature maps from the configuration
numFeatureMap(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils: Returns the number of feature maps for a given shape (must be at least 3 dimensions
numIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
numLabels() - Method in interface org.deeplearning4j.nn.api.Classifier: Returns the number of possible labels
numLabels() - Method in class org.deeplearning4j.nn.layers.OutputLayer: Returns the number of possible labels
numLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Returns the number of possible labels
numLineSearchIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
numLineSearchIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
numOutcomes - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
numParams() - Method in interface org.deeplearning4j.nn.api.Model: the number of parameters for the model
numParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer: The number of parameters for the model
numParams() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
numParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
numParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Returns a 1 x m vector where the vector is composed of a flattened vector of all of the weights for the various neuralNets and output layer
numParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
numtimesPredicted(int) - Method in class org.deeplearning4j.eval.Evaluation: Returns the number of times a given label was predicted
numTimesPredicted(int, int) - Method in class org.deeplearning4j.eval.Evaluation: Gets the number of times the given class was predicted for the given predicted label

O

objectIterator(ObjectInputStream) - Static method in class org.deeplearning4j.berkeley.Iterators
offer(E) - Method in class org.deeplearning4j.util.DiskBasedQueue
offset() - Method in class org.deeplearning4j.clustering.cluster.Point
oldScore - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
oneItemIterator(U) - Static method in class org.deeplearning4j.berkeley.Iterators
oneTailedFishersExact(int, int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath: Find a one-tailed Fisher's exact probability.
OptimisationStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
OptimisationStrategy(int, String) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
optimizationAlgo(OptimizationAlgorithm) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
optimizationAlgo - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
OptimizationAlgorithm - Enum in org.deeplearning4j.nn.api: Optimization algorithm to use
optimizationPhaseCondition - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
optimize() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
optimize(ClusteringOptimizationType, double) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
optimize() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Calls optimize
optimize(double, INDArray, INDArray) - Method in interface org.deeplearning4j.optimize.api.LineOptimizer: Line optimizer
optimize() - Method in class org.deeplearning4j.optimize.Solver
optimize(double, INDArray, INDArray) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
optimize() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer: Optimize call.
optimize() - Method in class org.deeplearning4j.optimize.solvers.IterationGradientDescent
optimize() - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
optimizer - Variable in class org.deeplearning4j.nn.layers.BaseLayer
optimizeWhenIterationCountMultipleOf(int) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
optimizeWhenPointDistributionVariationRateLessThan(double) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
ordering() - Method in class org.deeplearning4j.clustering.cluster.Point
org.deeplearning4j.base - package org.deeplearning4j.base
org.deeplearning4j.berkeley - package org.deeplearning4j.berkeley
org.deeplearning4j.clustering - package org.deeplearning4j.clustering
org.deeplearning4j.clustering.algorithm - package org.deeplearning4j.clustering.algorithm
org.deeplearning4j.clustering.algorithm.condition - package org.deeplearning4j.clustering.algorithm.condition
org.deeplearning4j.clustering.algorithm.iteration - package org.deeplearning4j.clustering.algorithm.iteration
org.deeplearning4j.clustering.algorithm.optimisation - package org.deeplearning4j.clustering.algorithm.optimisation
org.deeplearning4j.clustering.algorithm.strategy - package org.deeplearning4j.clustering.algorithm.strategy
org.deeplearning4j.clustering.cluster - package org.deeplearning4j.clustering.cluster
org.deeplearning4j.clustering.cluster.info - package org.deeplearning4j.clustering.cluster.info
org.deeplearning4j.clustering.kdtree - package org.deeplearning4j.clustering.kdtree
org.deeplearning4j.clustering.kmeans - package org.deeplearning4j.clustering.kmeans
org.deeplearning4j.clustering.quadtree - package org.deeplearning4j.clustering.quadtree
org.deeplearning4j.clustering.sptree - package org.deeplearning4j.clustering.sptree
org.deeplearning4j.clustering.vptree - package org.deeplearning4j.clustering.vptree: Created by agibsonccc on 1/3/15.
org.deeplearning4j.datasets - package org.deeplearning4j.datasets
org.deeplearning4j.datasets.canova - package org.deeplearning4j.datasets.canova
org.deeplearning4j.datasets.creator - package org.deeplearning4j.datasets.creator
org.deeplearning4j.datasets.fetchers - package org.deeplearning4j.datasets.fetchers
org.deeplearning4j.datasets.iterator - package org.deeplearning4j.datasets.iterator
org.deeplearning4j.datasets.iterator.impl - package org.deeplearning4j.datasets.iterator.impl
org.deeplearning4j.datasets.mnist - package org.deeplearning4j.datasets.mnist
org.deeplearning4j.datasets.mnist.draw - package org.deeplearning4j.datasets.mnist.draw
org.deeplearning4j.datasets.test - package org.deeplearning4j.datasets.test
org.deeplearning4j.datasets.vectorizer - package org.deeplearning4j.datasets.vectorizer
org.deeplearning4j.eval - package org.deeplearning4j.eval
org.deeplearning4j.exception - package org.deeplearning4j.exception
org.deeplearning4j.nn.api - package org.deeplearning4j.nn.api
org.deeplearning4j.nn.conf - package org.deeplearning4j.nn.conf
org.deeplearning4j.nn.conf.deserializers - package org.deeplearning4j.nn.conf.deserializers
org.deeplearning4j.nn.conf.distribution - package org.deeplearning4j.nn.conf.distribution
org.deeplearning4j.nn.conf.layers - package org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.conf.override - package org.deeplearning4j.nn.conf.override
org.deeplearning4j.nn.conf.preprocessor - package org.deeplearning4j.nn.conf.preprocessor
org.deeplearning4j.nn.conf.rng - package org.deeplearning4j.nn.conf.rng
org.deeplearning4j.nn.conf.serializers - package org.deeplearning4j.nn.conf.serializers
org.deeplearning4j.nn.conf.stepfunctions - package org.deeplearning4j.nn.conf.stepfunctions
org.deeplearning4j.nn.gradient - package org.deeplearning4j.nn.gradient
org.deeplearning4j.nn.layers - package org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.convolution - package org.deeplearning4j.nn.layers.convolution
org.deeplearning4j.nn.layers.convolution.preprocessor - package org.deeplearning4j.nn.layers.convolution.preprocessor
org.deeplearning4j.nn.layers.convolution.subsampling - package org.deeplearning4j.nn.layers.convolution.subsampling
org.deeplearning4j.nn.layers.factory - package org.deeplearning4j.nn.layers.factory
org.deeplearning4j.nn.layers.feedforward.autoencoder - package org.deeplearning4j.nn.layers.feedforward.autoencoder
org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive - package org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive
org.deeplearning4j.nn.layers.feedforward.rbm - package org.deeplearning4j.nn.layers.feedforward.rbm
org.deeplearning4j.nn.layers.recurrent - package org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.multilayer - package org.deeplearning4j.nn.multilayer
org.deeplearning4j.nn.params - package org.deeplearning4j.nn.params
org.deeplearning4j.nn.weights - package org.deeplearning4j.nn.weights
org.deeplearning4j.optimize - package org.deeplearning4j.optimize
org.deeplearning4j.optimize.api - package org.deeplearning4j.optimize.api
org.deeplearning4j.optimize.listeners - package org.deeplearning4j.optimize.listeners
org.deeplearning4j.optimize.solvers - package org.deeplearning4j.optimize.solvers
org.deeplearning4j.optimize.stepfunctions - package org.deeplearning4j.optimize.stepfunctions
org.deeplearning4j.optimize.terminations - package org.deeplearning4j.optimize.terminations
org.deeplearning4j.plot - package org.deeplearning4j.plot
org.deeplearning4j.plot.iterationlistener - package org.deeplearning4j.plot.iterationlistener
org.deeplearning4j.util - package org.deeplearning4j.util
output(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Classify input
output(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Label the probabilities of the input
OutputLayer - Class in org.deeplearning4j.nn.conf.layers: Output layer with different objective co-occurrences for different objectives.
OutputLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.OutputLayer
OutputLayer - Class in org.deeplearning4j.nn.layers: Output layer with different objective cooccurrences for different objectives.
OutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.OutputLayer
OutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.OutputLayer
OutputPreProcessor - Interface in org.deeplearning4j.nn.conf: Output pre processor's handle layer to layer interactions to ensure things like proper shape for input among other things.
override(ConfOverride) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
override(int, ConfOverride) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
overrideLayer(int, NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.override.ClassifierOverride
overrideLayer(int, NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.override.ComposableOverride
overrideLayer(int, NeuralNetConfiguration.Builder) - Method in interface org.deeplearning4j.nn.conf.override.ConfOverride: Override the builder configuration for a particular layer
overrideLayer(int, NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.override.LayerOverride

P

pack() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Packs a set of matrices in to one vector, where the matrices in this case are the w,hbias at each layer and the output layer w,bias
pack(List<Pair<INDArray, INDArray>>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Packs a set of matrices in to one vector
pad(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Return a String of length a minimum of totalChars characters by padding the input String str with spaces.
pad(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Pads the toString value of the given Object.
padLeft(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Pads the given String to the left with spaces to ensure that it's at least totalChars long.
padLeft(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
padLeft(int, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
padLeft(double, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
padOrTrim(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Pad or trim so as to produce a string of exactly a certain length.
padOrTrim(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Pad or trim the toString value of the given Object.
paintComponent(Graphics) - Method in class org.deeplearning4j.plot.FilterPanel
Pair<F,S> - Class in org.deeplearning4j.berkeley: A generic-typed pair of objects.
Pair(F, S) - Constructor for class org.deeplearning4j.berkeley.Pair
Pair.DefaultLexicographicPairComparator<F extends Comparable<F>,S extends Comparable<S>> - Class in org.deeplearning4j.berkeley
Pair.FirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
Pair.LexicographicPairComparator<F,S> - Class in org.deeplearning4j.berkeley
Pair.ReverseFirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
Pair.ReverseSecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
Pair.SecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
parallelCounterMap() - Static method in class org.deeplearning4j.berkeley.CounterMap: Returns a thread safe counter map
parallelTasks(List<Runnable>, ExecutorService) - Static method in class org.deeplearning4j.util.MultiThreadUtils
ParamInitializer - Interface in org.deeplearning4j.nn.api: Param initializer for a layer
paramInitializer - Variable in class org.deeplearning4j.nn.layers.BaseLayer
paramInitializer - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
paramInitializer - Variable in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
params() - Method in interface org.deeplearning4j.nn.api.Model: Parameters of the model (if any)
params - Variable in class org.deeplearning4j.nn.layers.BaseLayer
params() - Method in class org.deeplearning4j.nn.layers.BaseLayer: Returns the parameters of the neural network
params() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer: Returns the parameters of the neural network
params() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer: Returns the parameters of the neural network
params() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Returns a 1 x m vector where the vector is composed of a flattened vector of all of the weights for the various neuralNets(w,hbias NOT VBIAS) and output layer
params() - Method in class org.deeplearning4j.plot.BarnesHutTsne
PARAMS_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
paramTable() - Method in interface org.deeplearning4j.nn.api.Model: The param table
paramTable() - Method in class org.deeplearning4j.nn.layers.BaseLayer
paramTable() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
paramTable() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
paramTable() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
paramTable() - Method in class org.deeplearning4j.plot.BarnesHutTsne
parent(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
parent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns the parent of the passed in tree via traversal
parent() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
parse(String, Class<E>) - Static method in class org.deeplearning4j.util.EnumUtil
parseCommandLineArguments(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils: A simpler form of command line argument parsing.
partitionVariable(List<Double>, int) - Static method in class org.deeplearning4j.util.MathUtils: This will partition the given whole variable data applyTransformToDestination in to the specified chunk number.
peek() - Method in class org.deeplearning4j.berkeley.PriorityQueue
peek() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Returns the highest-priority element in the queue, but does not pop it.
peek() - Method in class org.deeplearning4j.util.DiskBasedQueue
pennPOSToWordnetPOS(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Computes the WordNet 2.0 POS tag corresponding to the PTB POS tag s.
permutation(double, double) - Static method in class org.deeplearning4j.util.MathUtils: This returns the permutation of n choose r.
permute(int...) - Method in class org.deeplearning4j.clustering.cluster.Point
perplexity(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
perplexity - Variable in class org.deeplearning4j.plot.Tsne.Builder
perplexity(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
perplexity - Variable in class org.deeplearning4j.plot.Tsne
plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.BarnesHutTsne: Plot tsne
plot(INDArray, int, List<String>) - Method in class org.deeplearning4j.plot.Tsne: Plot tsne (write the coordinates file)
plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.Tsne: Plot tsne
plotActivations(Layer) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
plotNetworkGradient(Layer, INDArray, int) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
plotNetworkGradient(Layer, Gradient, int) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
Point - Class in org.deeplearning4j.clustering.cluster
Point(INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
Point(String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
Point(String, String, double[]) - Constructor for class org.deeplearning4j.clustering.cluster.Point
Point(String, String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
point(INDArray) - Static method in class org.deeplearning4j.clustering.kdtree.HyperRect
PointClassification - Class in org.deeplearning4j.clustering.cluster
PointClassification(Cluster, double, boolean) - Constructor for class org.deeplearning4j.clustering.cluster.PointClassification
poll() - Method in class org.deeplearning4j.util.DiskBasedQueue
positive() - Method in class org.deeplearning4j.eval.Evaluation: Returns all of the positive guesses: true positive + false negative
postFirstStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
postFirstStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
postStep() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: After the step has been made, do an action
postStep() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer: Post step (conjugate gradient among other methods needs this)
postStep() - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
postStep() - Method in class org.deeplearning4j.optimize.solvers.GradientAscent
postStep() - Method in class org.deeplearning4j.optimize.solvers.IterationGradientDescent
postStep() - Method in class org.deeplearning4j.optimize.solvers.LBFGS
precision() - Method in class org.deeplearning4j.eval.Evaluation: Total precision based on guesses so far
precision(int) - Method in class org.deeplearning4j.eval.Evaluation: Returns the precision for a given label
predict(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Takes in a list of examples For each row, returns a label
predict(INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
predict(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Returns the predictions for each example in the dataset
predict(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM: Prediction with beam search
predict(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Returns the predictions for each example in the dataset
prediction() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
preFirstStepProcess(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
preFirstStepProcess(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
preOutput(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer: Raw activations
preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer: Classify input
preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
prependToEach(String, int) - Method in class org.deeplearning4j.util.StringGrid
preProcess(INDArray) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor: Pre process input for a multi layer network
preProcess(INDArray) - Method in interface org.deeplearning4j.nn.conf.OutputPreProcessor: Used for handling pre processing of layer output.
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.AggregatePreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableOutputPostProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVariancePrePreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePrePreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.preprocessor.ConvolutionInputPreProcessor
preProcess(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.preprocessor.ConvolutionPostProcessor
preProcessLine(INDArray) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Pre process a line before an iteration
preProcessLine(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer: Pre process the line (scaling and the like)
preProcessLine(INDArray) - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
preProcessLine(INDArray) - Method in class org.deeplearning4j.optimize.solvers.GradientAscent
preProcessLine(INDArray) - Method in class org.deeplearning4j.optimize.solvers.IterationGradientDescent
preProcessLine(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
preProcessor - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
preProcessor(Integer, OutputPreProcessor) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
PreProcessorDeSerializer - Class in org.deeplearning4j.nn.conf.deserializers: Created by agibsonccc on 2/11/15.
PreProcessorDeSerializer() - Constructor for class org.deeplearning4j.nn.conf.deserializers.PreProcessorDeSerializer
preProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
preProcessors(Map<Integer, OutputPreProcessor>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
PreProcessorSerializer - Class in org.deeplearning4j.nn.conf.serializers: Created by agibsonccc on 2/11/15.
PreProcessorSerializer() - Constructor for class org.deeplearning4j.nn.conf.serializers.PreProcessorSerializer
pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder: Whether to do pre train or not
pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
pretrain(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: This unsupervised learning method runs contrastive divergence on each RBM layer in the network.
pretrain(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: This unsupervised learning method runs contrastive divergence on each RBM layer in the network.
PretrainLayerFactory - Class in org.deeplearning4j.nn.layers.factory: Used for creating pretrain neural net layers
PretrainLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.PretrainLayerFactory
PretrainParamInitializer - Class in org.deeplearning4j.nn.params: Pretrain weight initializer.
PretrainParamInitializer() - Constructor for class org.deeplearning4j.nn.params.PretrainParamInitializer
prev() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: Move to the previous entry.
prevImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Move the cursor to the previous image.
printConfiguration() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Prints the configuration
printStringOneCharPerLine(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
printThreadInfo(PrintWriter, String) - Static method in class org.deeplearning4j.util.ReflectionUtils: Print all of the thread's information and stack traces.
printToFile(File, String, boolean) - Static method in class org.deeplearning4j.berkeley.StringUtils: Prints to a file.
printToFile(File, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Prints to a file.
printToFile(String, String, boolean) - Static method in class org.deeplearning4j.berkeley.StringUtils: Prints to a file.
printToFile(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Prints to a file.
PriorityQueue<E> - Class in org.deeplearning4j.berkeley: A priority queue based on a binary heap.
PriorityQueue() - Constructor for class org.deeplearning4j.berkeley.PriorityQueue
PriorityQueue(int) - Constructor for class org.deeplearning4j.berkeley.PriorityQueue
PriorityQueueInterface<E> - Interface in org.deeplearning4j.berkeley
probRound(double, Random) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the next nearest integer value in a probabilistic fashion (e.g.
probToLogOdds(double) - Static method in class org.deeplearning4j.util.MathUtils: Returns the log-odds for a given probability.
processors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
prod(int) - Method in class org.deeplearning4j.clustering.cluster.Point
propDown(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Calculates the activation of the hidden: activation(h * W + vbias)
propUp(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Calculates the activation of the visible : sigmoid(v * W + hbias)
pruneKeysBelowThreshold(double) - Method in class org.deeplearning4j.berkeley.Counter
put(E, double, boolean) - Method in class org.deeplearning4j.berkeley.Counter: Set the count for the given key if it is larger than the previous one;
put(E, double) - Method in class org.deeplearning4j.berkeley.PriorityQueue
put(E, double) - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Adds a key to the queue with the given priority.
put(NDArrayIndex[], INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
put(NDArrayIndex[], Number) - Method in class org.deeplearning4j.clustering.cluster.Point
put(int[], INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
put(int, int, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
put(int, int, Number) - Method in class org.deeplearning4j.clustering.cluster.Point
put(int, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
put(Pair<K, T>, V) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Associates the specified value with the specified key in this map (optional operation).
put(K, T, V) - Method in class org.deeplearning4j.util.MultiDimensionalMap
putAll(Map<? extends Pair<K, T>, ? extends V>) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Copies all of the mappings from the specified map to this map (optional operation).
putColumn(int, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
putRow(int, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int, double) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int, float) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int[], double) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int[], float) - Method in class org.deeplearning4j.clustering.cluster.Point
putScalar(int[], int) - Method in class org.deeplearning4j.clustering.cluster.Point
putSlice(int, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point

Q

QuadTree - Class in org.deeplearning4j.clustering.quadtree: QuadTree: http://en.wikipedia.org/wiki/Quadtree Reference impl based on the paper by: http://arxiv.org/pdf/1301.3342v2.pdf Primarily focused on 2 dimensions, may expand later if there's a reason.
QuadTree(INDArray) - Constructor for class org.deeplearning4j.clustering.quadtree.QuadTree: Pass in a matrix
QuadTree(QuadTree, INDArray, Cell) - Constructor for class org.deeplearning4j.clustering.quadtree.QuadTree
QuadTree(Cell) - Constructor for class org.deeplearning4j.clustering.quadtree.QuadTree

R

r - Static variable in class org.deeplearning4j.plot.Tsne
Random - Class in org.deeplearning4j.nn.conf.rng: An abstract random number generator.
Random() - Constructor for class org.deeplearning4j.nn.conf.rng.Random
randomDoubleBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
randomFloatBetween(float, float) - Static method in class org.deeplearning4j.util.MathUtils
randomNumberBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Generates a random integer between the specified numbers
randomNumberBetween(double, double, RandomGenerator) - Static method in class org.deeplearning4j.util.MathUtils: Generates a random integer between the specified numbers
Randoms - Class in org.deeplearning4j.nn.conf.rng
Randoms() - Constructor for class org.deeplearning4j.nn.conf.rng.Randoms
ravel() - Method in class org.deeplearning4j.clustering.cluster.Point
RawMnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl: Mnist data with scaled pixels
RawMnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.RawMnistDataSetIterator
RBM - Class in org.deeplearning4j.nn.conf.layers: Restricted Boltzmann Machine.
RBM() - Constructor for class org.deeplearning4j.nn.conf.layers.RBM
RBM - Class in org.deeplearning4j.nn.layers.feedforward.rbm: Restricted Boltzmann Machine.
RBM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
RBM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
RBM.HiddenUnit - Enum in org.deeplearning4j.nn.conf.layers
RBM.VisibleUnit - Enum in org.deeplearning4j.nn.conf.layers
RBMUtil - Class in org.deeplearning4j.util: Handles various cooccurrences for RBM specific cooccurrences
rdiv(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiv(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiv(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiv(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiv(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiv(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivi(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiviColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdiviRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rdivRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Reads the image at the current position.
readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Reads the current image.
readjustToData() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile: Reads the integer at the current position.
readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Reads the current label.
readObject(File) - Static method in class org.deeplearning4j.util.SerializationUtils
readObject(InputStream) - Static method in class org.deeplearning4j.util.SerializationUtils: Reads an object from the given input stream
readString(DataInputStream, int) - Static method in class org.deeplearning4j.util.ByteUtil
realMin - Variable in class org.deeplearning4j.plot.Tsne.Builder
realMin - Variable in class org.deeplearning4j.plot.Tsne
recall() - Method in class org.deeplearning4j.eval.Evaluation: Returns the recall for the outcomes
recall(int) - Method in class org.deeplearning4j.eval.Evaluation
reconstruct(INDArray, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Reconstructs the input.
ReconstructionDataSetIterator - Class in org.deeplearning4j.datasets.iterator: Wraps a data applyTransformToDestination iterator setting the first (feature matrix) as the labels.
ReconstructionDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
RecordReaderDataSetIterator - Class in org.deeplearning4j.datasets.canova: Record reader dataset iterator
RecordReaderDataSetIterator(RecordReader, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, WritableConverter) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
RECURRENT_WEIGHTS - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
RecursiveAutoEncoder - Class in org.deeplearning4j.nn.conf.layers: Recursive AutoEncoder.
RecursiveAutoEncoder() - Constructor for class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder
RecursiveAutoEncoder - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive: Recursive AutoEncoder.
RecursiveAutoEncoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
RecursiveAutoEncoderLayerFactory - Class in org.deeplearning4j.nn.layers.factory: Recursive parameter initializer
RecursiveAutoEncoderLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.RecursiveAutoEncoderLayerFactory
RecursiveParamInitializer - Class in org.deeplearning4j.nn.params: Recursive autoencoder initializer
RecursiveParamInitializer() - Constructor for class org.deeplearning4j.nn.params.RecursiveParamInitializer
reductionRatio(INDArray, double, double, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
ReflectionUtils - Class in org.deeplearning4j.util: General reflection utils
ReflectionUtils() - Constructor for class org.deeplearning4j.util.ReflectionUtils
refreshClusterCenter(Cluster, ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
refreshClustersCenters(ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
regularization(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
relativeDifferance(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
remove() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
remove() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
remove() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
remove() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
remove() - Method in class org.deeplearning4j.berkeley.PriorityQueue
remove() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Not supported -- next() already removes the head of the queue.
remove() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
remove(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
remove() - Method in class org.deeplearning4j.util.DiskBasedQueue
remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Removes the mapping for a key from this map if it is present (optional operation).
remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Removes the specified element from this applyTransformToDestination if it is present (optional operation).
removeAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
removeAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Removes from this applyTransformToDestination all of its elements that are contained in the specified collection (optional operation).
removeClusterInfos(List<Cluster>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
removeColumns(Integer...) - Method in class org.deeplearning4j.util.StringGrid: Removes the specified columns from the grid
removeEmptyClusters(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
removeEmptyClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
removeFirst() - Method in class org.deeplearning4j.berkeley.PriorityQueue
removeKey(E) - Method in class org.deeplearning4j.berkeley.Counter
removeKey(K) - Method in class org.deeplearning4j.berkeley.CounterMap
removeKeyFromEntries(E) - Method in class org.deeplearning4j.berkeley.Counter
removePoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
removePoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
removePoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
removePoints() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
removePoints() - Method in class org.deeplearning4j.clustering.Cluster
removePoints() - Method in class org.deeplearning4j.clustering.ClusterSet
removeRowsWithEmptyColumn(int) - Method in class org.deeplearning4j.util.StringGrid: Removes all rows with a column of NONE
removeRowsWithEmptyColumn(int, String) - Method in class org.deeplearning4j.util.StringGrid: Removes all rows with a column of missingValue
render(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
renderActivations(int, int, INDArray, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer
renderFilter(INDArray) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
renderFilters(INDArray, String, int, int, int) - Method in class org.deeplearning4j.plot.FilterRenderer: Once the probability image and weight histograms are behaving satisfactorily, we plot the learned filter for each hidden neuron, one per column of W.
renderHiddenBiases(int, int, INDArray, String) - Method in class org.deeplearning4j.plot.FilterRenderer
renderHistogram(INDArray, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer: Groups values into 1 of 10 bins, sums, and renders NOTE: this is "render histogram BS code"; - I'm not exactly concerned with how pretty it is.
repmat(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
reset() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
reset() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
reset() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
reset() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Returns the fetcher back to the beginning of the dataset
reset() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Resets the iterator back to the beginning
reset() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Resets the iterator back to the beginning
reset() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
resetAdaGradIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
resetAdaGradIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
resetLinearView() - Method in class org.deeplearning4j.clustering.cluster.Point
reshape(int...) - Method in class org.deeplearning4j.clustering.cluster.Point
reshape(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
ReshapePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Reshape post processor
ReshapePreProcessor(int...) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
retainAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
retainAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Retains only the elements in this applyTransformToDestination that are contained in the specified collection (optional operation).
reverse() - Method in class org.deeplearning4j.berkeley.Pair
ReverseFirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
ReverseSecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
rightChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
rng(Random) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
rng - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
rootMeansSquaredError(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the root mean squared error of two data sets
round(double, int, int) - Static method in class org.deeplearning4j.plot.FilterRenderer
round(double) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the next nearest integer value.
roundDouble(double, int) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the given number of decimal places.
roundFloat(float, int) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the given number of decimal places.
rows() - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
rsub(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubi(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubiColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubiRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
rsubRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
runPairWise(List<V>, CounterMap.CountFunction<V>) - Static method in class org.deeplearning4j.berkeley.CounterMap: Build a counter map by iterating pairwise over the list.

S

sample(Random) - Method in class org.deeplearning4j.berkeley.Counter: Will return a sample from the counter, will throw exception if any of the counts are < 0.0 or if the totalCount() <= 0.0
sample() - Method in class org.deeplearning4j.berkeley.Counter: Will return a sample from the counter, will throw exception if any of the counts are < 0.0 or if the totalCount() <= 0.0
sampleDoublesInInterval(double[][], int) - Static method in class org.deeplearning4j.util.MathUtils
sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork: Sample the hidden distribution given the visible
sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Binomial sampling of the hidden values given visible
sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork: Sample the visible distribution given the hidden
sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Guess the visible values given the hidden
SamplingDataSetIterator - Class in org.deeplearning4j.datasets.iterator: A wrapper for a dataset to sample from.
SamplingDataSetIterator(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
saveImageToDisk(BufferedImage, String) - Static method in class org.deeplearning4j.plot.FilterRenderer
saveObject(Object, File) - Static method in class org.deeplearning4j.util.SerializationUtils
saveToDisk(String) - Method in class org.deeplearning4j.plot.FilterRenderer
scale(double) - Method in class org.deeplearning4j.berkeley.Counter
scale(double) - Method in class org.deeplearning4j.berkeley.CounterMap: Scale all entries in CounterMap by scaleFactor
scaledClone(double) - Method in class org.deeplearning4j.berkeley.Counter
scatter(String[], INDArray[]) - Method in class org.deeplearning4j.plot.NeuralNetPlotter: Histograms the given matrices.
score(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier: Sets the input and labels and returns a score for the prediction wrt true labels
score(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Returns the f1 score for the given examples.
score() - Method in interface org.deeplearning4j.nn.api.Model: The score for the model
score - Variable in class org.deeplearning4j.nn.layers.BaseLayer
score() - Method in class org.deeplearning4j.nn.layers.BaseLayer
score() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
score() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
score() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
score() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
score() - Method in class org.deeplearning4j.nn.layers.OutputLayer: Objective function: the specified objective
score(DataSet) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Sets the input and labels and returns a score for the prediction wrt true labels
score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Returns the f1 score for the given examples.
score() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels and returns a score for the prediction wrt true labels
score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels and returns a score for the prediction wrt true labels
score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels and returns a score for the prediction wrt true labels
score() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Score of the model (relative to the objective function)
score(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Score of the model (relative to the objective function)
score() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: The score for the optimizer so far
score - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
score() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
score() - Method in class org.deeplearning4j.plot.BarnesHutTsne
SCORE_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
ScoreIterationListener - Class in org.deeplearning4j.optimize.listeners: Score iteration listener
ScoreIterationListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
ScoreIterationListener() - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
search(DataPoint, int, List<DataPoint>, List<Double>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
search(VPTree.Node, DataPoint, int, PriorityQueue<HeapItem>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
searchState - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
secondaryStride() - Method in class org.deeplearning4j.clustering.cluster.Point
SecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.SecondComparator
select(int, String) - Method in class org.deeplearning4j.util.StringGrid
SequenceClassifier - Interface in org.deeplearning4j.nn.api: Created by agibsonccc on 8/27/14.
SerializationUtils - Class in org.deeplearning4j.util: Serialization utils for saving and reading serializable objects
SerializationUtils() - Constructor for class org.deeplearning4j.util.SerializationUtils
serialize(OutputPreProcessor, JsonGenerator, SerializerProvider) - Method in class org.deeplearning4j.nn.conf.serializers.PreProcessorSerializer
setAbsTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch: Sets the tolerance of absolute diff in function value.
setAccumulation(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
setActivationFunction(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setAllCounts(double) - Method in class org.deeplearning4j.berkeley.Counter: Sets all counts to the given value, but does not remove any keys
setAllowEmptyClusters(boolean) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setApplySparsity(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setArray(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
setAveragePointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
setBackward(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setBatchSize(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setBatchSize(int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Set the batch size for the optimizer
setBatchSize(int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
setBegin(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setBoundary(Cell) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
setCenter(INDArray) - Method in class org.deeplearning4j.clustering.Cluster
setCenterOfMass(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setCluster(Cluster) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
setClusters(List<Cluster>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
setClusters(List<Cluster>) - Method in class org.deeplearning4j.clustering.ClusterSet
setClusterSetInfo(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
setClustersInfos(Map<String, ClusterInfo>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
setConf(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.Model: Setter for the configuration
setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.BaseLayer
setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.plot.BarnesHutTsne
setConfs(List<NeuralNetConfiguration>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setConstrainGradientToUnitNorm(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setContentionTracing(boolean) - Static method in class org.deeplearning4j.util.ReflectionUtils
setConvolutionType(ConvolutionDownSampleLayer.ConvolutionType) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setCorner(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
setCorner(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
setCorruptionLevel(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter: Set the count for the given key, clobbering any previous count.
setCount(K, V, double) - Method in class org.deeplearning4j.berkeley.CounterMap: Sets the count for a particular (key, value) pair.
setCounter(K, Counter<V>) - Method in class org.deeplearning4j.berkeley.CounterMap
setCumSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setCumSize(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
setCurrent(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Set the position to be read.
setCurrentIndex(long) - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile: Set the required current entry index.
setD(int) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
setDampingFactor(double) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setData(DataBuffer) - Method in class org.deeplearning4j.clustering.cluster.Point
setData(float[]) - Method in class org.deeplearning4j.clustering.cluster.Point
setDefault(double) - Method in class org.deeplearning4j.berkeley.CounterMap
setDeflt(double) - Method in class org.deeplearning4j.berkeley.Counter
setDirty(boolean) - Method in class org.deeplearning4j.berkeley.Counter
setDist(Distribution) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setDistance(double) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
setDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
setDistanceFunction(String) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setDistanceFunction(Class<? extends Accumulation>) - Method in class org.deeplearning4j.clustering.ClusterSet
setDistances(CounterMap<DataPoint, DataPoint>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
setDistancesBetweenClustersCenters(Table<String, String, Double>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
setDropOut(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setEnd(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setError(double) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setFeatureMapSize(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setFilterSize(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setFinalMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setFinalMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
setFirst(F) - Method in class org.deeplearning4j.berkeley.Pair
setFirst(S) - Method in class org.deeplearning4j.berkeley.Triple
setFirstKey(K) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
setGoldLabel(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setHeadWord(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setHh(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
setHiddenLayerSizes(int[]) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setHiddenUnit(RBM.HiddenUnit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setHw(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
setId(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
setId(String) - Method in class org.deeplearning4j.clustering.cluster.Point
setIndex(int) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
setIndex(int) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
setIndex(int) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
setIndex(int) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
setInitialClusterCount(Integer) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setInitialMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setInitialMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
setInput(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Note that if input isn't null and the neuralNets are null, this is a way of initializing the neural network
setItems(List<DataPoint>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
setIterationListener(IterationListener) - Method in class org.deeplearning4j.plot.Tsne
setIterationListeners(Collection<IterationListener>) - Method in interface org.deeplearning4j.nn.api.Layer: Set the iteration listeners for this layer.
setIterationListeners(Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.BaseLayer
setIterationListeners(Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setIterationListeners(Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setIterationsInfos(Map<Integer, IterationInfo>) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
setK(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setKernel(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setL1(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setL2(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setLabel(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
setLabel(String) - Method in class org.deeplearning4j.clustering.cluster.Point
setLabel(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setLabels(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
setLabels(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setLayer(Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setLayers(Layer[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setLayerWiseConfigurations(MultiLayerConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setLeaf(boolean) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setLeft(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
setLeft(VPTree.Node) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
setListeners(List<IterationListener>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setLogMetaInstability(double) - Method in class org.deeplearning4j.util.Viterbi
setLogOfDiangnalTProb(double) - Method in class org.deeplearning4j.util.Viterbi
setLogPCorrect(double) - Method in class org.deeplearning4j.util.Viterbi
setLogPIncorrect(double) - Method in class org.deeplearning4j.util.Viterbi
setLogStates(double) - Method in class org.deeplearning4j.util.Viterbi
setLossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setLower(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
setLr(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setMask(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setMax(double) - Method in class org.deeplearning4j.util.SummaryStatistics
setMaxCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter: Set's the key's count to the maximum of the current count and val.
setMaxIter(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setMaxIter(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
setMaxIterations(int) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
setMaxPointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
setMean(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
setMean(double) - Method in class org.deeplearning4j.util.SummaryStatistics
setMetaStability(double) - Method in class org.deeplearning4j.util.Viterbi
setMin(double) - Method in class org.deeplearning4j.util.SummaryStatistics
setMinCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter: Set's the key's count to the minimum of the current count and val.
setMinimize(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setMomentum(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
setMomentumAfter(Map<Integer, Double>) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setNewLocation(boolean) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
setnIn(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setNorthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setNorthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setnOut(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setNumChildren(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
setNumIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setNumLineSearchIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setOptimizationAlgo(OptimizationAlgorithm) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setOptimizationPhaseCondition(ClusteringAlgorithmCondition) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setParam(String, INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Set the parameter with a new ndarray
setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setParam(String, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setParam(String, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
setParameters(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets parameters for the model.
setParams(INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Set the parameters for this model.
setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Set the parameters for this model.
setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
setParams(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Set the parameters for this model.
setParams(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
setParamTable(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.Model: Setter for the param table
setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.BaseLayer
setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.plot.BarnesHutTsne
setParent(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
setParent(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setParent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setParse(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setpCorrect(double) - Method in class org.deeplearning4j.util.Viterbi
setPoint(INDArray) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
setPointDistanceFromCenterVariance(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
setPointDistancesFromCenter(Map<String, Double>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
setPointDistribution(Map<String, String>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
setPointLocationChange(AtomicInteger) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
setPoints(List<Point>) - Method in class org.deeplearning4j.clustering.cluster.Cluster
setPoints(List<INDArray>) - Method in class org.deeplearning4j.clustering.Cluster
setPossibleLabels(INDArray) - Method in class org.deeplearning4j.util.Viterbi
setPrediction(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
setPretrain(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setProbabilityOfSuccess(double) - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
setProcessors(Map<Integer, OutputPreProcessor>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setProperties(Object, Properties) - Static method in class org.deeplearning4j.util.Dl4jReflection: Sets the properties of the given object
setRealMin(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setRealMin(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
setRelTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch: Sets the tolerance of relative diff in function value.
setResetAdaGradIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setRight(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
setRight(VPTree.Node) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
setRng(Random) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setScore() - Method in interface org.deeplearning4j.nn.api.Model: Update the score
setScore() - Method in class org.deeplearning4j.nn.layers.BaseLayer
setScore() - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
setScore() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
setScore() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
setScore() - Method in class org.deeplearning4j.nn.layers.OutputLayer
setScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
setScore() - Method in class org.deeplearning4j.plot.BarnesHutTsne
setSecond(S) - Method in class org.deeplearning4j.berkeley.Pair
setSecond(T) - Method in class org.deeplearning4j.berkeley.Triple
setSecondKey(T) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
setSeed(long) - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
setSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setSouthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setSouthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
setSparsity(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setStates(int) - Method in class org.deeplearning4j.util.Viterbi
setStd(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
setStepFunction(StepFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setStpmax(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
setStrategyApplied(boolean) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
setStride(int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
setStride(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setSum(double) - Method in class org.deeplearning4j.util.SummaryStatistics
setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
setTags(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setTerminationCondition(ClusteringAlgorithmCondition) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setThird(U) - Method in class org.deeplearning4j.berkeley.Triple
setThreshold(double) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
setTokens(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setTotalPointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
setType(ClusteringOptimizationType) - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
setType(ClusteringStrategyType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
setType(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setup(ClusteringStrategy) - Static method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
setup(int, String) - Static method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
setup(int, String) - Static method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
setup(int, int, String) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
setup(int, double, String, boolean) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
setup(Configuration) - Method in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
setUpper(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
setupSearchState(Pair<Gradient, Double>) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Based on the gradient and score setup a search state
setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer: Setup the initial search state
setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.GradientAscent
setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
setUseAdaGrad(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setUseDropConnect(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setUseGaussNewtonVectorProductBackProp(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setUseRBMPropUpAsActivations(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
setUseRegularization(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
SetUtils - Class in org.deeplearning4j.util
setValue(double) - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
setValue(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setValue(V) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry: Replaces the value corresponding to this entry with the specified value (optional operation).
setVariables(List<String>) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setVector(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
setVisibleUnit(RBM.VisibleUnit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setWeightInit(WeightInit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setWeightShape(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
setWidth(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
setWidth(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
setX(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
setY(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
setY(INDArray) - Method in class org.deeplearning4j.plot.Tsne
shape() - Method in class org.deeplearning4j.clustering.cluster.Point
sigma - Variable in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
sigmoid(double) - Static method in class org.deeplearning4j.util.MathUtils: 1 / 1 + exp(-x)
simpleHostname(String) - Static method in class org.deeplearning4j.util.StringUtils: Given a full hostname, return the word upto the first dot.
size() - Method in class org.deeplearning4j.berkeley.Counter: The number of entries in the counter (not the total count -- use totalCount() instead).
size() - Method in class org.deeplearning4j.berkeley.CounterMap: The number of keys in this CounterMap (not the number of key-value entries -- use totalSize() for that)
size() - Method in class org.deeplearning4j.berkeley.PriorityQueue
size() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Number of elements in the queue.
size(int) - Method in class org.deeplearning4j.clustering.cluster.Point
size() - Method in class org.deeplearning4j.clustering.kdtree.KDTree: The number of elements in the tree
size() - Method in class org.deeplearning4j.util.DiskBasedQueue
size() - Method in class org.deeplearning4j.util.Index
size() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns the number of key-value mappings in this map.
size() - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns the number of elements in this applyTransformToDestination (its cardinality).
SizeComparator() - Constructor for class org.deeplearning4j.util.StringCluster.SizeComparator
slice(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
slice(int) - Method in class org.deeplearning4j.clustering.cluster.Point
slices() - Method in class org.deeplearning4j.clustering.cluster.Point
sliceVectors(List<INDArray>) - Method in class org.deeplearning4j.clustering.cluster.Point
slope(double, double, double, double) - Method in class org.deeplearning4j.util.MathUtils: This returns the slope of the given points.
SloppyMath - Class in org.deeplearning4j.berkeley: The class SloppyMath contains methods for performing basic numeric operations.
SloppyMath() - Constructor for class org.deeplearning4j.berkeley.SloppyMath
slurpFile(File) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given File.
slurpFile(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given file with the given encoding.
slurpFile(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given file
slurpFileNoExceptions(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given file with the given encoding.
slurpFileNoExceptions(File) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given File.
slurpFileNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text in the given File.
slurpGBFile(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
slurpGBFileNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
slurpGBURL(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpGBURLNoExceptions(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpReader(Reader) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text from the given Reader.
slurpURL(URL, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpURL(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpURL(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpURLNoExceptions(URL, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpURLNoExceptions(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
slurpURLNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns all the text at the given URL.
sm(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Tests if a is smaller than b.
SMALL - Static variable in class org.deeplearning4j.util.MathUtils: The small deviation allowed in double comparisons.
Solver - Class in org.deeplearning4j.optimize: Generic purpose solver
Solver() - Constructor for class org.deeplearning4j.optimize.Solver
Solver.Builder - Class in org.deeplearning4j.optimize
sort() - Method in class org.deeplearning4j.util.StringCluster
sortBy(int) - Method in class org.deeplearning4j.util.StringGrid
sortColumnsByWordLikelihoodIncluded(int) - Method in class org.deeplearning4j.util.StringGrid
sparsity(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
split(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Splits on whitespace (\\s+).
split(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Splits the given string using the given regex as delimiters.
split(int, String) - Method in class org.deeplearning4j.util.StringGrid
split(String) - Static method in class org.deeplearning4j.util.StringUtils: Split a string using the default separator
split(String, char, char) - Static method in class org.deeplearning4j.util.StringUtils: Split a string using the given separator
splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitInputs(INDArray, INDArray, List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, double) - Static method in class org.deeplearning4j.util.InputSplit
splitInputs(List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, double) - Static method in class org.deeplearning4j.util.InputSplit
splitMostPopulatedClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
splitOnCharWithQuoting(String, char, char, char) - Static method in class org.deeplearning4j.berkeley.StringUtils: This function splits the String s into multiple Strings using the splitChar.
SpTree - Class in org.deeplearning4j.clustering.sptree
SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
SpTree(INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
SpTree(INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
SpTree(INDArray) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
squaredDistance(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
squaredLoss(double[], double[], double, double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the squared loss of the given points
ssError(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: How much of the variance is NOT explained by the regression
ssReg(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: How much of the variance is explained by the regression
ssTotal(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: Total variance in target attribute
start() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
start() - Method in class org.deeplearning4j.plot.FilterRenderer
STATE_TRACKER_CONNECTION_STRING - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
stats() - Method in class org.deeplearning4j.eval.Evaluation
std(int) - Method in class org.deeplearning4j.clustering.cluster.Point
step(INDArray, INDArray, Object[]) - Method in interface org.deeplearning4j.optimize.api.StepFunction: Step with the given parameters
step(INDArray, INDArray) - Method in interface org.deeplearning4j.optimize.api.StepFunction: Step with no parameters
step() - Method in interface org.deeplearning4j.optimize.api.StepFunction
step - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
step(INDArray, INDArray, Object[]) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
step() - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
step(INDArray, INDArray, Object[]) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
step() - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
step(INDArray, INDArray, Object[]) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
step(INDArray, INDArray, Object[]) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
step(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne: An individual iteration
step(INDArray, int) - Method in class org.deeplearning4j.plot.Tsne: An individual iteration
stepFunction(StepFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
stepFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
StepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions: Custom step function for line search.
StepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.StepFunction
StepFunction - Interface in org.deeplearning4j.optimize.api: Custom step function for line search
stepFunction - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
StepFunctions - Class in org.deeplearning4j.optimize.stepfunctions
StepFunctions() - Constructor for class org.deeplearning4j.optimize.stepfunctions.StepFunctions
StochasticHessianFree - Class in org.deeplearning4j.optimize.solvers: Hessian Free Optimization by Ryan Kiros http://www.cs.toronto.edu/~rkiros/papers/shf13.pdf
StochasticHessianFree(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticHessianFree
StochasticHessianFree(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticHessianFree
stopLyingIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
stopLyingIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne
stpMax - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
stride() - Method in class org.deeplearning4j.clustering.cluster.Point
stride(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
string2long(String) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix: Convert a string to long.
StringCluster - Class in org.deeplearning4j.util: Clusters strings based on fingerprint: for example Two words and TWO words or WORDS TWO would be put together
StringCluster(List<String>) - Constructor for class org.deeplearning4j.util.StringCluster
StringCluster.SizeComparator - Class in org.deeplearning4j.util
StringGrid - Class in org.deeplearning4j.util: String matrix
StringGrid(StringGrid) - Constructor for class org.deeplearning4j.util.StringGrid
StringGrid(String, int) - Constructor for class org.deeplearning4j.util.StringGrid
StringGrid(String, Collection<String>) - Constructor for class org.deeplearning4j.util.StringGrid
stringifyException(Throwable) - Static method in class org.deeplearning4j.util.StringUtils: Make a string representation of the exception.
stringSimilarity(String...) - Static method in class org.deeplearning4j.util.MathUtils: Calculate string similarity with tfidf weights relative to each character frequency and how many times a character appears in a given string
stringToProperties(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: This method converts a comma-separated String (with whitespace optionally allowed after the comma) representing properties to a Properties object.
stringToURI(String[]) - Static method in class org.deeplearning4j.util.StringUtils
StringUtils - Class in org.deeplearning4j.berkeley: StringUtils is a class for random String things.
StringUtils - Class in org.deeplearning4j.util: General string utils
StringUtils() - Constructor for class org.deeplearning4j.util.StringUtils
StringUtils.TraditionalBinaryPrefix - Enum in org.deeplearning4j.util: The traditional binary prefixes, kilo, mega, ..., exa, which can be represented by a 64-bit integer.
stripDuplicateRows() - Method in class org.deeplearning4j.util.StringGrid
stripNonAlphaNumerics(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
sub(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
sub(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
sub(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
sub(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
sub(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
sub(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subArray(int[], int[], int[]) - Method in class org.deeplearning4j.clustering.cluster.Point
subColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subDivide() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Create four children which fully divide this cell into four quads of equal area
subDivide() - Method in class org.deeplearning4j.clustering.sptree.SpTree: Subdivide the node in to 4 children
subi(Number) - Method in class org.deeplearning4j.clustering.cluster.Point
subi(Number, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subi(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subi(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subi(IComplexNumber) - Method in class org.deeplearning4j.clustering.cluster.Point
subi(IComplexNumber, IComplexNDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subiColumnVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subiRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
subRowVector(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
SubsampleLayerFactory - Class in org.deeplearning4j.nn.layers.factory
SubsampleLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.SubsampleLayerFactory
SubsampleParamInitializer - Class in org.deeplearning4j.nn.params
SubsampleParamInitializer() - Constructor for class org.deeplearning4j.nn.params.SubsampleParamInitializer
SubsamplingLayer - Class in org.deeplearning4j.nn.conf.layers
SubsamplingLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
SubsamplingLayer - Class in org.deeplearning4j.nn.layers.convolution.subsampling: Subsampling layer.
SubsamplingLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
sum(int) - Method in class org.deeplearning4j.clustering.cluster.Point
sum(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the sum of the given array.
SummaryStatistics - Class in org.deeplearning4j.util
summaryStats(INDArray) - Static method in class org.deeplearning4j.util.SummaryStatistics
summaryStatsString(INDArray) - Static method in class org.deeplearning4j.util.SummaryStatistics
sumOfMeanDifferences(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: Used for calculating top part of simple regression for beta 1
sumOfMeanDifferencesOnePoint(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Used for calculating top part of simple regression for beta 1
sumOfProducts(double[]...) - Static method in class org.deeplearning4j.util.MathUtils: This returns the sum of products for the given numbers.
sumOfSquares(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the sum of squares for the given vector.
swap(int, int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
swap(int, int) - Method in class org.deeplearning4j.util.StringGrid
swapAxes(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne
symbol - Variable in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
symmetrized(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne: Symmetrize the value matrix

T

tags() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
terminate(double, double, Object[]) - Method in interface org.deeplearning4j.optimize.api.TerminationCondition: Whether to terminate based on the given metadata
terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.EpsTermination
terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.Norm2Termination
terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.ZeroDirection
terminationCondition - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
TerminationCondition - Interface in org.deeplearning4j.optimize.api: Created by agibsonccc on 12/24/14.
terminationConditions - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
TerminationConditions - Class in org.deeplearning4j.optimize.terminations: Created by agibsonccc on 12/24/14.
TerminationConditions() - Constructor for class org.deeplearning4j.optimize.terminations.TerminationConditions
TestDataSetIterator - Class in org.deeplearning4j.datasets.test: Track number of times the dataset iterator has been called
TestDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.test.TestDataSetIterator
tf(int) - Static method in class org.deeplearning4j.util.MathUtils: Term frequency: 1+ log10(count)
tfidf(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Return td * idf
theta(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
thread(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators: Executes calls to next() in a different thread
times(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the product of all numbers in the given array.
TimeSeriesUtils - Class in org.deeplearning4j.util: Basic time series utils
TimeSeriesUtils() - Constructor for class org.deeplearning4j.util.TimeSeriesUtils
title - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
title - Variable in class org.deeplearning4j.plot.FilterRenderer
toArray() - Method in class org.deeplearning4j.util.DiskBasedQueue
toArray(T[]) - Method in class org.deeplearning4j.util.DiskBasedQueue
toArray() - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns an array containing all of the elements in this applyTransformToDestination.
toArray(T[]) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Returns an array containing all of the elements in this applyTransformToDestination; the runtime type of the returned array is that of the specified array.
toBufferedImage(Image) - Static method in class org.deeplearning4j.util.ImageLoader: Converts a given Image into a BufferedImage
toByteArray(Serializable) - Static method in class org.deeplearning4j.util.SerializationUtils: Converts the given object to a byte array
toCSV() - Method in class org.deeplearning4j.eval.ConfusionMatrix: Outputs the ConfusionMatrix as comma-separated values for easy import into spreadsheets
toDecimal(String) - Static method in class org.deeplearning4j.util.MathUtils: This will convert the given binary string to a decimal based integer
toHTML() - Method in class org.deeplearning4j.eval.ConfusionMatrix: Outputs Confusion Matrix in an HTML table.
toImage(INDArray) - Static method in class org.deeplearning4j.util.ImageLoader
toJson() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
toJson() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Return this configuration as json
tolerance(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
tolerance - Variable in class org.deeplearning4j.plot.Tsne.Builder
tolerance(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
tolerance - Variable in class org.deeplearning4j.plot.Tsne
toLines() - Method in class org.deeplearning4j.util.StringGrid
toLogSpace() - Method in class org.deeplearning4j.berkeley.Counter
toPoints(List<INDArray>) - Static method in class org.deeplearning4j.clustering.cluster.Point
toString() - Method in class org.deeplearning4j.berkeley.Counter: Returns a string representation with the keys ordered by decreasing counts.
toString(int) - Method in class org.deeplearning4j.berkeley.Counter: Returns a string representation which includes no more than the maxKeysToPrint elements with largest counts.
toString(int, boolean) - Method in class org.deeplearning4j.berkeley.Counter: Returns a string representation which includes no more than the maxKeysToPrint elements with largest counts and optionally prints one element per line.
toString(int) - Method in class org.deeplearning4j.berkeley.CounterMap
toString() - Method in class org.deeplearning4j.berkeley.CounterMap
toString(Collection<String>) - Method in class org.deeplearning4j.berkeley.CounterMap
toString() - Method in class org.deeplearning4j.berkeley.Pair
toString() - Method in class org.deeplearning4j.berkeley.PriorityQueue: Returns a representation of the queue in decreasing priority order.
toString(int, boolean) - Method in class org.deeplearning4j.berkeley.PriorityQueue: Returns a representation of the queue in decreasing priority order, displaying at most maxKeysToPrint elements and optionally printing one element per line.
toString() - Method in class org.deeplearning4j.berkeley.Triple
toString() - Method in class org.deeplearning4j.eval.ConfusionMatrix
toString() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
toString() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
toString() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
toString() - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
toString() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer
toString() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
toString() - Method in class org.deeplearning4j.nn.conf.layers.LSTM
toString() - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer
toString() - Method in class org.deeplearning4j.nn.conf.layers.RBM
toString() - Method in class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder
toString() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
toString() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
toString() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
toString() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
toString() - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
toString() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
toString() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
toString() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
toString() - Method in class org.deeplearning4j.util.Index
toString() - Method in class org.deeplearning4j.util.MultiDimensionalMap
toString() - Method in class org.deeplearning4j.util.SummaryStatistics
toStringSortedByKeys() - Method in class org.deeplearning4j.berkeley.Counter
toStringTabSeparated() - Method in class org.deeplearning4j.berkeley.Counter
totalCount() - Method in class org.deeplearning4j.berkeley.Counter: Finds the total of all counts in the counter.
totalCount() - Method in class org.deeplearning4j.berkeley.CounterMap: Returns the total of all counts in sub-counters.
totalExamples() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
totalExamples - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
totalExamples() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
totalExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
totalExamples() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: The total number of examples
totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
totalExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Total examples in the iterator
totalExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Total examples in the iterator
totalExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
totalExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
totalOutcomes() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
totalOutcomes() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
totalOutcomes() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: The number of labels for a dataset
totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: The number of labels for the dataset
totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: The number of labels for the dataset
totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
totalOutcomes() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
totalSize() - Method in class org.deeplearning4j.berkeley.CounterMap: Returns the total number of (key, value) entries in the CounterMap (not their total counts).
trainingFileLabelsFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
trainingFilesFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
Transform(Iterator<S>) - Constructor for class org.deeplearning4j.berkeley.Iterators.Transform
transform(S) - Method in class org.deeplearning4j.berkeley.Iterators.Transform
transform(INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Transform the data based on the model's output.
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM: Reconstructs the visible input.
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer: Transform the data based on the model's output.
transform(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
transform(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Transform the data based on the model's output.
transform(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
TransformingIterator(Iterator<I>, MyMethod<I, O>) - Constructor for class org.deeplearning4j.berkeley.Iterators.TransformingIterator
transpose() - Method in class org.deeplearning4j.clustering.cluster.Point
transpose() - Method in interface org.deeplearning4j.nn.api.Layer: Return a transposed copy of the weights/bias (this means reverse the number of inputs and outputs on the weights)
transpose() - Method in class org.deeplearning4j.nn.layers.BaseLayer
transpose() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
transpose() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
transpose() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
transposei() - Method in class org.deeplearning4j.clustering.cluster.Point
Tree - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive: Tree for a recursive neural tensor network based on Socher et al's work.
Tree(Tree) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Clone constructor (all but the children)
Tree(Tree, List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
Tree(List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
TreeMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
treeSet() - Static method in class org.deeplearning4j.util.MultiDimensionalSet
trim(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns s if it's at most maxWidth chars, otherwise chops right side to fit.
trim(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
Triple<S,T,U> - Class in org.deeplearning4j.berkeley
Triple(S, T, U) - Constructor for class org.deeplearning4j.berkeley.Triple
trueNegatives() - Method in class org.deeplearning4j.eval.Evaluation: True negatives: correctly rejected
truncate(int, int, int) - Static method in class org.deeplearning4j.berkeley.StringUtils: This returns a string from decimal digit smallestDigit to decimal digit biggest digit.
Tsne - Class in org.deeplearning4j.plot: Tsne calculation
Tsne() - Constructor for class org.deeplearning4j.plot.Tsne
Tsne(int, double, double, double, double, int, boolean, boolean, int, double, double, boolean, double, double) - Constructor for class org.deeplearning4j.plot.Tsne
Tsne.Builder - Class in org.deeplearning4j.plot
type - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
type() - Method in interface org.deeplearning4j.nn.api.Layer: Returns the layer type
type() - Method in class org.deeplearning4j.nn.layers.BaseLayer
type() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionDownSampleLayer
type() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
type() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
type() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
typeForFactory(NeuralNetConfiguration) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories: Get the type for the layer factory

U

U - Static variable in class org.deeplearning4j.nn.params.RecursiveParamInitializer
unEscapeString(String) - Static method in class org.deeplearning4j.util.StringUtils: Unescape commas in the string using the default escape char
unEscapeString(String, char, char) - Static method in class org.deeplearning4j.util.StringUtils: Unescape charToEscape in the string with the escape char escapeChar
unEscapeString(String, char, char[]) - Static method in class org.deeplearning4j.util.StringUtils
uniform(Random, double, double) - Static method in class org.deeplearning4j.util.MathUtils: Generate a uniform random number from the given rng
uniformBasedOnInAndOut(int[], int, int) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Generate a random matrix with respect to the number of inputs and outputs.
UniformDistribution - Class in org.deeplearning4j.nn.conf.distribution: A uniform distribution.
UniformDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.UniformDistribution: Create a uniform real distribution using the given lower and upper bounds.
union(Set<? extends T>, Set<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils
UnitVariancePrePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Unit variance operation
UnitVariancePrePreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.UnitVariancePrePreProcessor
unPack(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Unpacks a parameter matrix in to a transform of pairs(w,hbias) triples with layer wise
unsafeAdd(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
unsafeSubtract(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
untarFile(File, File) - Method in class org.deeplearning4j.base.LFWLoader
untarFile(File, File) - Method in class org.deeplearning4j.base.MnistFetcher
unzipFileTo(String, String) - Static method in class org.deeplearning4j.util.ArchiveUtils: Extracts files to the specified destination
update(Gradient) - Method in interface org.deeplearning4j.nn.api.Model: Perform one update applying the gradient
update(Gradient) - Method in class org.deeplearning4j.nn.layers.BaseLayer
update(Gradient) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
update(Gradient) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
update(Gradient) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
update(Gradient) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
update(MultiLayerNetwork) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Assigns the parameters of this model to the ones specified by this network.
update(Gradient) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
update(Gradient) - Method in class org.deeplearning4j.plot.BarnesHutTsne
updateGradientAccordingToParams(Gradient, Model, int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Update the gradient according to the configuration such as adagrad, momentum, and sparsity
updateGradientAccordingToParams(INDArray, INDArray, int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer: Update the gradient according to the configuration such as adagrad, momentum, and sparsity
updateGradientAccordingToParams(NeuralNetConfiguration, int, Gradient, int, Map<String, AdaGrad>, Model) - Static method in class org.deeplearning4j.optimize.GradientAdjustment: Updates each variable wrt its gradient
updateGradientAccordingToParams(NeuralNetConfiguration, int, AdaGrad, INDArray, INDArray, int) - Static method in class org.deeplearning4j.optimize.GradientAdjustment: Update the gradient according to the configuration such as adagrad, momentum, and sparsity
updateGradientAccordingToParams(INDArray, INDArray, int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer: Update the gradient according to the configuration such as adagrad, momentum, and sparsity
updateGradientAccordingToParams(Gradient, Model, int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
uriToString(URI[]) - Static method in class org.deeplearning4j.util.StringUtils
useAdaGrad(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
useAdaGrad(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
useAdaGrad - Variable in class org.deeplearning4j.plot.Tsne.Builder
useAdaGrad(boolean) - Method in class org.deeplearning4j.plot.Tsne.Builder
useAdaGrad - Variable in class org.deeplearning4j.plot.Tsne
useDropConnect - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
useDropConnect(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder: Whether to use drop connect or not
useDropConnect - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
useGaussNewtonVectorProductBackProp - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
usePca(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
usePca - Variable in class org.deeplearning4j.plot.Tsne.Builder
usePca(boolean) - Method in class org.deeplearning4j.plot.Tsne.Builder
usePca - Variable in class org.deeplearning4j.plot.Tsne
useRBMPropUpAsActivations - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
useRBMPropUpAsActivations(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
useRBMPropUpAsActivations - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
useRegularization - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration

V

validateInput() - Method in interface org.deeplearning4j.nn.api.Model: Validate the input
validateInput() - Method in class org.deeplearning4j.nn.layers.BaseLayer
validateInput() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
validateInput() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
validateInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
validateInput() - Method in class org.deeplearning4j.plot.BarnesHutTsne
value() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
value - Variable in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
valueOf(String) - Static method in enum org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimizationType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategyType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.api.Layer.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer.ConvolutionType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.HiddenUnit: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.VisibleUnit: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.nn.weights.WeightInit: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix: Returns the enum constant of this type with the specified name.
valueOf(char) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
values() - Static method in enum org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimizationType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategyType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.api.Layer.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer.ConvolutionType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.HiddenUnit: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.VisibleUnit: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.nn.weights.WeightInit: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.deeplearning4j.util.MultiDimensionalMap: Returns a Collection view of the values contained in this map.
values() - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix: Returns an array containing the constants of this enum type, in the order they are declared.
var(int) - Method in class org.deeplearning4j.clustering.cluster.Point
variables - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
variables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
variance(double[]) - Static method in class org.deeplearning4j.util.MathUtils
VarianceVariationCondition - Class in org.deeplearning4j.clustering.algorithm.condition
VarianceVariationCondition(Condition, int) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
varianceVariationLessThan(double, int) - Static method in class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
vector() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
vectorAlongDimension(int, int) - Method in class org.deeplearning4j.clustering.cluster.Point
vectorize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
vectorize() - Method in interface org.deeplearning4j.datasets.vectorizer.Vectorizer: Vectorizes the input source in to a dataset
Vectorizer - Interface in org.deeplearning4j.datasets.vectorizer: A Vectorizer at its essence takes an input source and converts it to a matrix for neural network consumption.
vectorLength(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Returns the vector length (sqrt(sum(x_i))
vectorsAlongDimension(int) - Method in class org.deeplearning4j.clustering.cluster.Point
VISIBLE_BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.PretrainParamInitializer
visibleUnit(RBM.VisibleUnit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
Viterbi - Class in org.deeplearning4j.util: Based on the impl from: https://gist.github.com/rmcgibbo/3915977
Viterbi(INDArray) - Constructor for class org.deeplearning4j.util.Viterbi: The possible outcomes for the chain.
VPTree - Class in org.deeplearning4j.clustering.vptree: Vantage point tree implementation
VPTree(INDArray, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(INDArray, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(INDArray) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree(List<DataPoint>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
VPTree.Node - Class in org.deeplearning4j.clustering.vptree

W

W - Static variable in class org.deeplearning4j.nn.params.RecursiveParamInitializer
w_0(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils
w_1(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils
WeakHashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.WeakHashMapFactory
WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.DefaultParamInitializer
weightInit(WeightInit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
weightInit - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
WeightInit - Enum in org.deeplearning4j.nn.weights: Weight initialization scheme
WeightInitUtil - Class in org.deeplearning4j.nn.weights: Weight initialization utility
WeightInitUtil() - Constructor for class org.deeplearning4j.nn.weights.WeightInitUtil
weightMatrices(MultiLayerNetwork) - Static method in class org.deeplearning4j.util.MultiLayerUtil: Return the weight matrices for a multi layer network
weightsFor(List<Double>) - Static method in class org.deeplearning4j.util.MathUtils: This returns the minimized loss values for a given vector.
weightsFor(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the minimized loss values for a given vector.
weightShape(int[]) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
width(int) - Method in class org.deeplearning4j.clustering.sptree.Cell
width() - Method in class org.deeplearning4j.clustering.sptree.Cell
windows() - Method in class org.deeplearning4j.util.MovingWindowMatrix: Returns a list of non flattened moving window matrices
windows(boolean) - Method in class org.deeplearning4j.util.MovingWindowMatrix: Moving window, capture a row x column moving window of a given matrix
writeImageToPpm(int[][], String) - Static method in class org.deeplearning4j.datasets.mnist.MnistManager: Writes the given image in the given file using the PPM data format.
writeLinesTo(String) - Method in class org.deeplearning4j.util.StringGrid
writeMatrix(INDArray) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
writeObject(Serializable, OutputStream) - Static method in class org.deeplearning4j.util.SerializationUtils: Writes the object to the output stream THIS DOES NOT FLUSH THE STREAM

X

xVals(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the x values of the given vector.

Y

y - Variable in class org.deeplearning4j.plot.Tsne
Y_GRAD - Static variable in class org.deeplearning4j.plot.BarnesHutTsne
yield() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree: Returns all of the labels for this node and all of its children (recursively)
yIncs - Variable in class org.deeplearning4j.plot.Tsne
yVals(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the odd indexed values for the given vector

Z

ZeroDirection - Class in org.deeplearning4j.optimize.terminations: Absolute magnitude of gradient is 0
ZeroDirection() - Constructor for class org.deeplearning4j.optimize.terminations.ZeroDirection
ZeroMeanAndUnitVariancePrePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Zero mean and unit variance operation
ZeroMeanAndUnitVariancePrePreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePrePreProcessor
ZeroMeanPrePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: Zero mean and unit variance operation
ZeroMeanPrePreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
zip(Iterator<S>, Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators

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